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Poole, Mackworth & Goebel 1998, p. 1. Russell & Norvig 2003, p. 55. Definition of AI as the study of intelligent agents: Poole, Mackworth & Goebel (1998), which provides the version that is used in this article. These authors use the term "computational intelligence" as a synonym for artificial intelligence.[1] Russell & Norvig (2003) (who prefer the term "rational agent") and write "The whole-agent view is now widely accepted in the field".[2] Nilsson 1998 Legg & Hutter 2007 Russell & Norvig 2009, p. 2. McCorduck 2004, p. 204 Maloof, Mark. "Artificial Intelligence: An Introduction, p. 37" (PDF). georgetown.edu. Archived (PDF) from the original on 25 August 2018. "How AI Is Getting Groundbreaking Changes In Talent Management And HR Tech". Hackernoon. Archived from the original on 11 September 2019. Retrieved 14 February 2020. Schank, Roger C. (1991). "Where's the AI". AI magazine. Vol. 12 no. 4. p. 38. Russell & Norvig 2009. "AlphaGo – Google DeepMind". Archived from the original on 10 March 2016. Allen, Gregory (April 2020). "Department of Defense Joint AI Center - Understanding AI Technology" (PDF). AI.mil - The official site of the Department of Defense Joint Artificial Intelligence Center. Archived (PDF) from the original on 21 April 2020. Retrieved 25 April 2020. Optimism of early AI: * Herbert Simon quote: Simon 1965, p. 96 quoted in Crevier 1993, p. 109. * Marvin Minsky quote: Minsky 1967, p. 2 quoted in Crevier 1993, p. 109. Boom of the 1980s: rise of expert systems, Fifth Generation Project, Alvey, MCC, SCI: * McCorduck 2004, pp. 426–441 * Crevier 1993, pp. 161–162,197–203, 211, 240 * Russell & Norvig 2003, p. 24 * NRC 1999, pp. 210–211 * Newquist 1994, pp. 235–248 First AI Winter, Mansfield Amendment, Lighthill report * Crevier 1993, pp. 115–117 * Russell & Norvig 2003, p. 22 * NRC 1999, pp. 212–213 * Howe 1994 * Newquist 1994, pp. 189–201 Second AI winter: * McCorduck 2004, pp. 430–435 * Crevier 1993, pp. 209–210 * NRC 1999, pp. 214–216 * Newquist 1994, pp. 301–318 AI becomes hugely successful in the early 21st century * Clark 2015 Pamela McCorduck (2004, p. 424) writes of "the rough shattering of AI in subfields—vision, natural language, decision theory, genetic algorithms, robotics ... and these with own sub-subfield—that would hardly have anything to say to each other." This list of intelligent traits is based on the topics covered by the major AI textbooks, including: * Russell & Norvig 2003 * Luger & Stubblefield 2004 * Poole, Mackworth & Goebel 1998 * Nilsson 1998 Kolata 1982. Maker 2006. Biological intelligence vs. intelligence in general: Russell & Norvig 2003, pp. 2–3, who make the analogy with aeronautical engineering. McCorduck 2004, pp. 100–101, who writes that there are "two major branches of artificial intelligence: one aimed at producing intelligent behavior regardless of how it was accomplished, and the other aimed at modeling intelligent processes found in nature, particularly human ones." Kolata 1982, a paper in Science, which describes McCarthy's indifference to biological models. Kolata quotes McCarthy as writing: "This is AI, so we don't care if it's psychologically real".[19] McCarthy recently reiterated his position at the AI@50 conference where he said "Artificial intelligence is not, by definition, simulation of human intelligence".[20]. Neats vs. scruffies: * McCorduck 2004, pp. 421–424, 486–489 * Crevier 1993, p. 168 * Nilsson 1983, pp. 10–11 Symbolic vs. sub-symbolic AI: * Nilsson (1998, p. 7), who uses the term "sub-symbolic". General intelligence (strong AI) is discussed in popular introductions to AI: * Kurzweil 1999 and Kurzweil 2005 See the Dartmouth proposal, under Philosophy, below. McCorduck 2004, p. 34. McCorduck 2004, p. xviii. McCorduck 2004, p. 3. McCorduck 2004, pp. 340–400. This is a central idea of Pamela McCorduck's Machines Who Think. She writes: "I like to think of artificial intelligence as the scientific apotheosis of a venerable cultural tradition."[26] "Artificial intelligence in one form or another is an idea that has pervaded Western intellectual history, a dream in urgent need of being realized."[27] "Our history is full of attempts—nutty, eerie, comical, earnest, legendary and real—to make artificial intelligences, to reproduce what is the essential us—bypassing the ordinary means. Back and forth between myth and reality, our imaginations supplying what our workshops couldn't, we have engaged for a long time in this odd form of self-reproduction."[28] She traces the desire back to its Hellenistic roots and calls it the urge to "forge the Gods."[29] "Stephen Hawking believes AI could be mankind's last accomplishment". BetaNews. 21 October 2016. Archived from the original on 28 August 2017. Lombardo P, Boehm I, Nairz K (2020). "RadioComics – Santa Claus and the future of radiology". Eur J Radiol. 122 (1): 108771. doi:10.1016/j.ejrad.2019.108771. PMID 31835078. Ford, Martin; Colvin, Geoff (6 September 2015). "Will robots create more jobs than they destroy?". The Guardian. Archived from the original on 16 June 2018. Retrieved 13 January 2018. AI applications widely used behind the scenes: * Russell & Norvig 2003, p. 28 * Kurzweil 2005, p. 265 * NRC 1999, pp. 216–222 * Newquist 1994, pp. 189–201 AI in myth: * McCorduck 2004, pp. 4–5 * Russell & Norvig 2003, p. 939 AI in early science fiction. * McCorduck 2004, pp. 17–25 Formal reasoning: * Berlinski, David (2000). The Advent of the Algorithm. Harcourt Books. ISBN 978-0-15-601391-8. OCLC 46890682. Archived from the original on 26 July 2020. Retrieved 22 August 2020. Turing, Alan (1948), "Machine Intelligence", in Copeland, B. Jack (ed.), The Essential Turing: The ideas that gave birth to the computer age, Oxford: Oxford University Press, p. 412, ISBN 978-0-19-825080-7 Russell & Norvig 2009, p. 16. Dartmouth conference: * McCorduck 2004, pp. 111–136 * Crevier 1993, pp. 47–49, who writes "the conference is generally recognized as the official birthdate of the new science." * Russell & Norvig 2003, p. 17, who call the conference "the birth of artificial intelligence." * NRC 1999, pp. 200–201 McCarthy, John (1988). "Review of The Question of Artificial Intelligence". Annals of the History of Computing. 10 (3): 224–229., collected in McCarthy, John (1996). "10. Review of The Question of Artificial Intelligence". Defending AI Research: A Collection of Essays and Reviews. CSLI., p. 73, "[O]ne of the reasons for inventing the term "artificial intelligence" was to escape association with "cybernetics". Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert (not Robert) Wiener as a guru or having to argue with him." Hegemony of the Dartmouth conference attendees: * Russell & Norvig 2003, p. 17, who write "for the next 20 years the field would be dominated by these people and their students." * McCorduck 2004, pp. 129–130 Russell & Norvig 2003, p. 18. Schaeffer J. (2009) Didn't Samuel Solve That Game?. In: One Jump Ahead. Springer, Boston, MA Samuel, A. L. (July 1959). "Some Studies in Machine Learning Using the Game of Checkers". IBM Journal of Research and Development. 3 (3): 210–229. CiteSeerX 10.1.1.368.2254. doi:10.1147/rd.33.0210. "Golden years" of AI (successful symbolic reasoning programs 1956–1973): * McCorduck 2004, pp. 243–252 * Crevier 1993, pp. 52–107 * Moravec 1988, p. 9 * Russell & Norvig 2003, pp. 18–21 The programs described are Arthur Samuel's checkers program for the IBM 701, Daniel Bobrow's STUDENT, Newell and Simon's Logic Theorist and Terry Winograd's SHRDLU. DARPA pours money into undirected pure research into AI during the 1960s: * McCorduck 2004, p. 131 * Crevier 1993, pp. 51, 64–65 * NRC 1999, pp. 204–205 AI in England: * Howe 1994 Lighthill 1973. Expert systems: * ACM 1998, I.2.1 * Russell & Norvig 2003, pp. 22–24 * Luger & Stubblefield 2004, pp. 227–331 * Nilsson 1998, chpt. 17.4 * McCorduck 2004, pp. 327–335, 434–435 * Crevier 1993, pp. 145–62, 197–203 * Newquist 1994, pp. 155–183 Mead, Carver A.; Ismail, Mohammed (8 May 1989). Analog VLSI Implementation of Neural Systems (PDF). The Kluwer International Series in Engineering and Computer Science. 80. Norwell, MA: Kluwer Academic Publishers. doi:10.1007/978-1-4613-1639-8. ISBN 978-1-4613-1639-8. Archived from the original (PDF) on 6 November 2019. Retrieved 24 January 2020. Formal methods are now preferred ("Victory of the neats"): * Russell & Norvig 2003, pp. 25–26 * McCorduck 2004, pp. 486–487 McCorduck 2004, pp. 480–483. Markoff 2011. "Ask the AI experts: What's driving today's progress in AI?". McKinsey & Company. Archived from the original on 13 April 2018. Retrieved 13 April 2018. Administrator. "Kinect's AI breakthrough explained". i-programmer.info. Archived from the original on 1 February 2016. Rowinski, Dan (15 January 2013). "Virtual Personal Assistants & The Future Of Your Smartphone [Infographic]". ReadWrite. Archived from the original on 22 December 2015. "Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol". BBC News. 12 March 2016. Archived from the original on 26 August 2016. Retrieved 1 October 2016. Metz, Cade (27 May 2017). "After Win in China, AlphaGo's Designers Explore New AI". Wired. Archived from the original on 2 June 2017. "World's Go Player Ratings". May 2017. Archived from the original on 1 April 2017. "柯洁迎19岁生日 雄踞人类世界排名第一已两年" (in Chinese). May 2017. Archived from the original on 11 August 2017. Clark, Jack (8 December 2015). "Why 2015 Was a Breakthrough Year in Artificial Intelligence". Bloomberg News. Archived from the original on 23 November 2016. Retrieved 23 November 2016. After a half-decade of quiet breakthroughs in artificial intelligence, 2015 has been a landmark year. Computers are smarter and learning faster than ever. "Reshaping Business With Artificial Intelligence". MIT Sloan Management Review. Archived from the original on 19 May 2018. Retrieved 2 May 2018. Lorica, Ben (18 December 2017). "The state of AI adoption". O'Reilly Media. Archived from the original on 2 May 2018. Retrieved 2 May 2018. Allen, Gregory (6 February 2019). "Understanding China's AI Strategy". Center for a New American Security. Archived from the original on 17 March 2019. "Review | How two AI superpowers – the U.S. and China – battle for supremacy in the field". Washington Post. 2 November 2018. Archived from the original on 4 November 2018. Retrieved 4 November 2018. at 10:11, Alistair Dabbs 22 Feb 2019. "Artificial Intelligence: You know it isn't real, yeah?". www.theregister.co.uk. Archived from the original on 21 May 2020. Retrieved 22 August 2020. "Stop Calling it Artificial Intelligence". Archived from the original on 2 December 2019. Retrieved 1 December 2019. "AI isn't taking over the world – it doesn't exist yet". GBG Global website. Archived from the original on 11 August 2020. Retrieved 22 August 2020. Kaplan, Andreas; Haenlein, Michael (1 January 2019). "Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence". Business Horizons. 62 (1): 15–25. doi:10.1016/j.bushor.2018.08.004. Domingos 2015, Chapter 5. Domingos 2015, Chapter 7. Lindenbaum, M., Markovitch, S., & Rusakov, D. (2004). Selective sampling for nearest neighbor classifiers. Machine learning, 54(2), 125–152. Domingos 2015, Chapter 1. Intractability and efficiency and the combinatorial explosion: * Russell & Norvig 2003, pp. 9, 21–22 Domingos 2015, Chapter 2, Chapter 3. Hart, P. E.; Nilsson, N. J.; Raphael, B. (1972). "Correction to "A Formal Basis for the Heuristic Determination of Minimum Cost Paths"". SIGART Newsletter (37): 28–29. doi:10.1145/1056777.1056779. S2CID 6386648. Domingos 2015, Chapter 2, Chapter 4, Chapter 6. "Can neural network computers learn from experience, and if so, could they ever become what we would call 'smart'?". Scientific American. 2018. Archived from the original on 25 March 2018. Retrieved 24 March 2018. Domingos 2015, Chapter 6, Chapter 7. Domingos 2015, p. 286. "Single pixel change fools AI programs". BBC News. 3 November 2017. Archived from the original on 22 March 2018. Retrieved 12 March 2018. "AI Has a Hallucination Problem That's Proving Tough to Fix". WIRED. 2018. Archived from the original on 12 March 2018. Retrieved 12 March 2018. Matti, D.; Ekenel, H. K.; Thiran, J. P. (2017). Combining LiDAR space clustering and convolutional neural networks for pedestrian detection. 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). pp. 1–6. arXiv:1710.06160. doi:10.1109/AVSS.2017.8078512. ISBN 978-1-5386-2939-0. S2CID 2401976. Ferguson, Sarah; Luders, Brandon; Grande, Robert C.; How, Jonathan P. (2015). Real-Time Predictive Modeling and Robust Avoidance of Pedestrians with Uncertain, Changing Intentions. Algorithmic Foundations of Robotics XI. Springer Tracts in Advanced Robotics. 107. Springer, Cham. pp. 161–177. arXiv:1405.5581. doi:10.1007/978-3-319-16595-0_10. ISBN 978-3-319-16594-3. S2CID 8681101. "Cultivating Common Sense | DiscoverMagazine.com". Discover Magazine. 2017. Archived from the original on 25 March 2018. Retrieved 24 March 2018. Davis, Ernest; Marcus, Gary (24 August 2015). "Commonsense reasoning and commonsense knowledge in artificial intelligence". Communications of the ACM. 58 (9): 92–103. doi:10.1145/2701413. S2CID 13583137. Archived from the original on 22 August 2020. Retrieved 6 April 2020. Winograd, Terry (January 1972). "Understanding natural language". Cognitive Psychology. 3 (1): 1–191. doi:10.1016/0010-0285(72)90002-3. "Don't worry: Autonomous cars aren't coming tomorrow (or next year)". Autoweek. 2016. Archived from the original on 25 March 2018. Retrieved 24 March 2018. Knight, Will (2017). "Boston may be famous for bad drivers, but it's the testing ground for a smarter self-driving car". MIT Technology Review. Archived from the original on 22 August 2020. Retrieved 27 March 2018. Prakken, Henry (31 August 2017). "On the problem of making autonomous vehicles conform to traffic law". Artificial Intelligence and Law. 25 (3): 341–363. doi:10.1007/s10506-017-9210-0. Lieto, Antonio (May 2018). "The knowledge level in cognitive architectures: Current limitations and possible developments". Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Problem solving, puzzle solving, game playing and deduction: * Russell & Norvig 2003, chpt. 3–9, * Poole, Mackworth & Goebel 1998, chpt. 2,3,7,9, * Luger & Stubblefield 2004, chpt. 3,4,6,8, * Nilsson 1998, chpt. 7–12 Uncertain reasoning: * Russell & Norvig 2003, pp. 452–644, * Poole, Mackworth & Goebel 1998, pp. 345–395, * Luger & Stubblefield 2004, pp. 333–381, * Nilsson 1998, chpt. 19 Psychological evidence of sub-symbolic reasoning: * Wason & Shapiro (1966) showed that people do poorly on completely abstract problems, but if the problem is restated to allow the use of intuitive social intelligence, performance dramatically improves. (See Wason selection task) * Kahneman, Slovic & Tversky (1982) have shown that people are terrible at elementary problems that involve uncertain reasoning. (See list of cognitive biases for several examples). * Lakoff & Núñez (2000) have controversially argued that even our skills at mathematics depend on knowledge and skills that come from "the body", i.e. sensorimotor and perceptual skills. (See Where Mathematics Comes From) Knowledge representation: * ACM 1998, I.2.4, * Russell & Norvig 2003, pp. 320–363, * Poole, Mackworth & Goebel 1998, pp. 23–46, 69–81, 169–196, 235–277, 281–298, 319–345, * Luger & Stubblefield 2004, pp. 227–243, * Nilsson 1998, chpt. 18 Knowledge engineering: * Russell & Norvig 2003, pp. 260–266, * Poole, Mackworth & Goebel 1998, pp. 199–233, * Nilsson 1998, chpt. ≈17.1–17.4 Representing categories and relations: Semantic networks, description logics, inheritance (including frames and scripts): * Russell & Norvig 2003, pp. 349–354, * Poole, Mackworth & Goebel 1998, pp. 174–177, * Luger & Stubblefield 2004, pp. 248–258, * Nilsson 1998, chpt. 18.3 Representing events and time:Situation calculus, event calculus, fluent calculus (including solving the frame problem): * Russell & Norvig 2003, pp. 328–341, * Poole, Mackworth & Goebel 1998, pp. 281–298, * Nilsson 1998, chpt. 18.2 Causal calculus: * Poole, Mackworth & Goebel 1998, pp. 335–337 Representing knowledge about knowledge: Belief calculus, modal logics: * Russell & Norvig 2003, pp. 341–344, * Poole, Mackworth & Goebel 1998, pp. 275–277 Sikos, Leslie F. (June 2017). Description Logics in Multimedia Reasoning. Cham: Springer. doi:10.1007/978-3-319-54066-5. ISBN 978-3-319-54066-5. S2CID 3180114. Archived from the original on 29 August 2017. Ontology: * Russell & Norvig 2003, pp. 320–328 Smoliar, Stephen W.; Zhang, HongJiang (1994). "Content based video indexing and retrieval". IEEE Multimedia. 1 (2): 62–72. doi:10.1109/93.311653. S2CID 32710913. Neumann, Bernd; Möller, Ralf (January 2008). "On scene interpretation with description logics". Image and Vision Computing. 26 (1): 82–101. doi:10.1016/j.imavis.2007.08.013. Kuperman, G. J.; Reichley, R. M.; Bailey, T. C. (1 July 2006). "Using Commercial Knowledge Bases for Clinical Decision Support: Opportunities, Hurdles, and Recommendations". Journal of the American Medical Informatics Association. 13 (4): 369–371. doi:10.1197/jamia.M2055. PMC 1513681. PMID 16622160. MCGARRY, KEN (1 December 2005). "A survey of interestingness measures for knowledge discovery". The Knowledge Engineering Review. 20 (1): 39–61. doi:10.1017/S0269888905000408. S2CID 14987656. Bertini, M; Del Bimbo, A; Torniai, C (2006). "Automatic annotation and semantic retrieval of video sequences using multimedia ontologies". MM '06 Proceedings of the 14th ACM international conference on Multimedia. 14th ACM international conference on Multimedia. Santa Barbara: ACM. pp. 679–682. Qualification problem: * McCarthy & Hayes 1969 * Russell & Norvig 2003[page needed] While McCarthy was primarily concerned with issues in the logical representation of actions, Russell & Norvig 2003 apply the term to the more general issue of default reasoning in the vast network of assumptions underlying all our commonsense knowledge. Default reasoning and default logic, non-monotonic logics, circumscription, closed world assumption, abduction (Poole et al. places abduction under "default reasoning". Luger et al. places this under "uncertain reasoning"): * Russell & Norvig 2003, pp. 354–360, * Poole, Mackworth & Goebel 1998, pp. 248–256, 323–335, * Luger & Stubblefield 2004, pp. 335–363, * Nilsson 1998, ~18.3.3 Breadth of commonsense knowledge: * Russell & Norvig 2003, p. 21, * Crevier 1993, pp. 113–114, * Moravec 1988, p. 13, * Lenat & Guha 1989 (Introduction) Dreyfus & Dreyfus 1986. Gladwell 2005. Expert knowledge as embodied intuition: * Dreyfus & Dreyfus 1986 (Hubert Dreyfus is a philosopher and critic of AI who was among the first to argue that most useful human knowledge was encoded sub-symbolically. See Dreyfus' critique of AI) * Gladwell 2005 (Gladwell's Blink is a popular introduction to sub-symbolic reasoning and knowledge.) * Hawkins & Blakeslee 2005 (Hawkins argues that sub-symbolic knowledge should be the primary focus of AI research.) Planning: * ACM 1998, ~I.2.8, * Russell & Norvig 2003, pp. 375–459, * Poole, Mackworth & Goebel 1998, pp. 281–316, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Information value theory: * Russell & Norvig 2003, pp. 600–604 Classical planning: * Russell & Norvig 2003, pp. 375–430, * Poole, Mackworth & Goebel 1998, pp. 281–315, * Luger & Stubblefield 2004, pp. 314–329, * Nilsson 1998, chpt. 10.1–2, 22 Planning and acting in non-deterministic domains: conditional planning, execution monitoring, replanning and continuous planning: * Russell & Norvig 2003, pp. 430–449 Multi-agent planning and emergent behavior: * Russell & Norvig 2003, pp. 449–455 Turing 1950. Solomonoff 1956. Alan Turing discussed the centrality of learning as early as 1950, in his classic paper "Computing Machinery and Intelligence".[120] In 1956, at the original Dartmouth AI summer conference, Ray Solomonoff wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".[121] This is a form of Tom Mitchell's widely quoted definition of machine learning: "A computer program is set to learn from an experience E with respect to some task T and some performance measure P if its performance on T as measured by P improves with experience E." Learning: * ACM 1998, I.2.6, * Russell & Norvig 2003, pp. 649–788, * Poole, Mackworth & Goebel 1998, pp. 397–438, * Luger & Stubblefield 2004, pp. 385–542, * Nilsson 1998, chpt. 3.3, 10.3, 17.5, 20 Jordan, M. I.; Mitchell, T. M. (16 July 2015). "Machine learning: Trends, perspectives, and prospects". Science. 349 (6245): 255–260. Bibcode:2015Sci...349..255J. doi:10.1126/science.aaa8415. PMID 26185243. S2CID 677218. Reinforcement learning: * Russell & Norvig 2003, pp. 763–788 * Luger & Stubblefield 2004, pp. 442–449 Natural language processing: * ACM 1998, I.2.7 * Russell & Norvig 2003, pp. 790–831 * Poole, Mackworth & Goebel 1998, pp. 91–104 * Luger & Stubblefield 2004, pp. 591–632 "Versatile question answering systems: seeing in synthesis" Archived 1 February 2016 at the Wayback Machine, Mittal et al., IJIIDS, 5(2), 119–142, 2011 Applications of natural language processing, including information retrieval (i.e. text mining) and machine translation: * Russell & Norvig 2003, pp. 840–857, * Luger & Stubblefield 2004, pp. 623–630 Cambria, Erik; White, Bebo (May 2014). "Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]". IEEE Computational Intelligence Magazine. 9 (2): 48–57. doi:10.1109/MCI.2014.2307227. S2CID 206451986. Vincent, James (7 November 2019). "OpenAI has published the text-generating AI it said was too dangerous to share". The Verge. Archived from the original on 11 June 2020. Retrieved 11 June 2020. Machine perception: * Russell & Norvig 2003, pp. 537–581, 863–898 * Nilsson 1998, ~chpt. 6 Speech recognition: * ACM 1998, ~I.2.7 * Russell & Norvig 2003, pp. 568–578 Object recognition: * Russell & Norvig 2003, pp. 885–892 Computer vision: * ACM 1998, I.2.10 * Russell & Norvig 2003, pp. 863–898 * Nilsson 1998, chpt. 6 Robotics: * ACM 1998, I.2.9, * Russell & Norvig 2003, pp. 901–942, * Poole, Mackworth & Goebel 1998, pp. 443–460 Moving and configuration space: * Russell & Norvig 2003, pp. 916–932 Tecuci 2012. Robotic mapping (localization, etc): * Russell & Norvig 2003, pp. 908–915 Cadena, Cesar; Carlone, Luca; Carrillo, Henry; Latif, Yasir; Scaramuzza, Davide; Neira, Jose; Reid, Ian; Leonard, John J. (December 2016). "Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age". IEEE Transactions on Robotics. 32 (6): 1309–1332. arXiv:1606.05830. Bibcode:2016arXiv160605830C. doi:10.1109/TRO.2016.2624754. S2CID 2596787. Moravec, Hans (1988). Mind Children. Harvard University Press. p. 15. Chan, Szu Ping (15 November 2015). "This is what will happen when robots take over the world". Archived from the original on 24 April 2018. Retrieved 23 April 2018. "IKEA furniture and the limits of AI". The Economist. 2018. Archived from the original on 24 April 2018. Retrieved 24 April 2018. Kismet. Thompson, Derek (2018). "What Jobs Will the Robots Take?". The Atlantic. Archived from the original on 24 April 2018. Retrieved 24 April 2018. Scassellati, Brian (2002). "Theory of mind for a humanoid robot". Autonomous Robots. 12 (1): 13–24. doi:10.1023/A:1013298507114. S2CID 1979315. Cao, Yongcan; Yu, Wenwu; Ren, Wei; Chen, Guanrong (February 2013). "An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination". IEEE Transactions on Industrial Informatics. 9 (1): 427–438. arXiv:1207.3231. doi:10.1109/TII.2012.2219061. S2CID 9588126. Thro 1993. Edelson 1991. Tao & Tan 2005. Poria, Soujanya; Cambria, Erik; Bajpai, Rajiv; Hussain, Amir (September 2017). "A review of affective computing: From unimodal analysis to multimodal fusion". Information Fusion. 37: 98–125. doi:10.1016/j.inffus.2017.02.003. hdl:1893/25490. Emotion and affective computing: * Minsky 2006 Waddell, Kaveh (2018). "Chatbots Have Entered the Uncanny Valley". The Atlantic. Archived from the original on 24 April 2018. Retrieved 24 April 2018. Pennachin, C.; Goertzel, B. (2007). Contemporary Approaches to Artificial General Intelligence. Artificial General Intelligence. Cognitive Technologies. Cognitive Technologies. Berlin, Heidelberg: Springer. doi:10.1007/978-3-540-68677-4_1. ISBN 978-3-540-23733-4. Roberts, Jacob (2016). "Thinking Machines: The Search for Artificial Intelligence". Distillations. Vol. 2 no. 2. pp. 14–23. Archived from the original on 19 August 2018. Retrieved 20 March 2018. "The superhero of artificial intelligence: can this genius keep it in check?". the Guardian. 16 February 2016. Archived from the original on 23 April 2018. Retrieved 26 April 2018. Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis (26 February 2015). "Human-level control through deep reinforcement learning". Nature. 518 (7540): 529–533. Bibcode:2015Natur.518..529M. doi:10.1038/nature14236. PMID 25719670. S2CID 205242740. Sample, Ian (14 March 2017). "Google's DeepMind makes AI program that can learn like a human". the Guardian. Archived from the original on 26 April 2018. Retrieved 26 April 2018. "From not working to neural networking". The Economist. 2016. Archived from the original on 31 December 2016. Retrieved 26 April 2018. Domingos 2015. Artificial brain arguments: AI requires a simulation of the operation of the human brain * Russell & Norvig 2003, p. 957 * Crevier 1993, pp. 271 and 279 A few of the people who make some form of the argument: * Moravec 1988 * Kurzweil 2005, p. 262 * Hawkins & Blakeslee 2005 The most extreme form of this argument (the brain replacement scenario) was put forward by Clark Glymour in the mid-1970s and was touched on by Zenon Pylyshyn and John Searle in 1980. Goertzel, Ben; Lian, Ruiting; Arel, Itamar; de Garis, Hugo; Chen, Shuo (December 2010). "A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures". Neurocomputing. 74 (1–3): 30–49. doi:10.1016/j.neucom.2010.08.012. Nilsson 1983, p. 10. Nils Nilsson writes: "Simply put, there is wide disagreement in the field about what AI is all about."[163] AI's immediate precursors: * McCorduck 2004, pp. 51–107 * Crevier 1993, pp. 27–32 * Russell & Norvig 2003, pp. 15, 940 * Moravec 1988, p. 3 Haugeland 1985, pp. 112–117 The most dramatic case of sub-symbolic AI being pushed into the background was the devastating critique of perceptrons by Marvin Minsky and Seymour Papert in 1969. See History of AI, AI winter, or Frank Rosenblatt. Cognitive simulation, Newell and Simon, AI at CMU (then called Carnegie Tech): * McCorduck 2004, pp. 139–179, 245–250, 322–323 (EPAM) * Crevier 1993, pp. 145–149 Soar (history): * McCorduck 2004, pp. 450–451 * Crevier 1993, pp. 258–263 McCarthy and AI research at SAIL and SRI International: * McCorduck 2004, pp. 251–259 * Crevier 1993 AI research at Edinburgh and in France, birth of Prolog: * Crevier 1993, pp. 193–196 * Howe 1994 AI at MIT under Marvin Minsky in the 1960s : * McCorduck 2004, pp. 259–305 * Crevier 1993, pp. 83–102, 163–176 * Russell & Norvig 2003, p. 19 Cyc: * McCorduck 2004, p. 489, who calls it "a determinedly scruffy enterprise" * Crevier 1993, pp. 239–243 * Russell & Norvig 2003, p. 363−365 * Lenat & Guha 1989 Knowledge revolution: * McCorduck 2004, pp. 266–276, 298–300, 314, 421 * Russell & Norvig 2003, pp. 22–23 Frederick, Hayes-Roth; William, Murray; Leonard, Adelman. "Expert systems". AccessScience. doi:10.1036/1097-8542.248550. Embodied approaches to AI: * McCorduck 2004, pp. 454–462 * Brooks 1990 * Moravec 1988 Weng et al. 2001. Lungarella et al. 2003. Asada et al. 2009. Oudeyer 2010. Revival of connectionism: * Crevier 1993, pp. 214–215 * Russell & Norvig 2003, p. 25 Computational intelligence * IEEE Computational Intelligence Society Archived 9 May 2008 at the Wayback Machine Hutson, Matthew (16 February 2018). "Artificial intelligence faces reproducibility crisis". Science. pp. 725–726. Bibcode:2018Sci...359..725H. doi:10.1126/science.359.6377.725. Archived from the original on 29 April 2018. Retrieved 28 April 2018. Norvig 2012. Langley 2011. Katz 2012. The intelligent agent paradigm: * Russell & Norvig 2003, pp. 27, 32–58, 968–972 * Poole, Mackworth & Goebel 1998, pp. 7–21 * Luger & Stubblefield 2004, pp. 235–240 * Hutter 2005, pp. 125–126 The definition used in this article, in terms of goals, actions, perception and environment, is due to Russell & Norvig (2003). Other definitions also include knowledge and learning as additional criteria. Agent architectures, hybrid intelligent systems: * Russell & Norvig (2003, pp. 27, 932, 970–972) * Nilsson (1998, chpt. 25) Hierarchical control system: * Albus 2002 Lieto, Antonio; Lebiere, Christian; Oltramari, Alessandro (May 2018). "The knowledge level in cognitive architectures: Current limitations and possibile developments". Cognitive Systems Research. 48: 39–55. doi:10.1016/j.cogsys.2017.05.001. hdl:2318/1665207. S2CID 206868967. Lieto, Antonio; Bhatt, Mehul; Oltramari, Alessandro; Vernon, David (May 2018). "The role of cognitive architectures in general artificial intelligence". Cognitive Systems Research. 48: 1–3. doi:10.1016/j.cogsys.2017.08.003. hdl:2318/1665249. S2CID 36189683. Russell & Norvig 2009, p. 1. White Paper: On Artificial Intelligence - A European approach to excellence and trust (PDF). Brussels: European Commission. 2020. p. 1. Archived (PDF) from the original on 20 February 2020. Retrieved 20 February 2020. CNN 2006. Using AI to predict flight delays Archived 20 November 2018 at the Wayback Machine, Ishti.org. N. Aletras; D. Tsarapatsanis; D. Preotiuc-Pietro; V. Lampos (2016). "Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective". PeerJ Computer Science. 2: e93. doi:10.7717/peerj-cs.93. "The Economist Explains: Why firms are piling into artificial intelligence". The Economist. 31 March 2016. Archived from the original on 8 May 2016. Retrieved 19 May 2016. Lohr, Steve (28 February 2016). "The Promise of Artificial Intelligence Unfolds in Small Steps". The New York Times. Archived from the original on 29 February 2016. Retrieved 29 February 2016. Frangoul, Anmar (14 June 2019). "A Californian business is using A.I. to change the way we think about energy storage". CNBC. Archived from the original on 25 July 2020. Retrieved 5 November 2019. Wakefield, Jane (15 June 2016). "Social media 'outstrips TV' as news source for young people". BBC News. Archived from the original on 24 June 2016. Smith, Mark (22 July 2016). "So you think you chose to read this article?". BBC News. Archived from the original on 25 July 2016. Brown, Eileen. "Half of Americans do not believe deepfake news could target them online". ZDNet. Archived from the original on 6 November 2019. Retrieved 3 December 2019. The Turing test: Turing's original publication: * Turing 1950 Historical influence and philosophical implications: * Haugeland 1985, pp. 6–9 * Crevier 1993, p. 24 * McCorduck 2004, pp. 70–71 * Russell & Norvig 2003, pp. 2–3 and 948 Dartmouth proposal: * McCarthy et al. 1955 (the original proposal) * Crevier 1993, p. 49 (historical significance) The physical symbol systems hypothesis: * Newell & Simon 1976, p. 116 * McCorduck 2004, p. 153 * Russell & Norvig 2003, p. 18 Dreyfus 1992, p. 156. Dreyfus criticized the necessary condition of the physical symbol system hypothesis, which he called the "psychological assumption": "The mind can be viewed as a device operating on bits of information according to formal rules."[206] Dreyfus' critique of artificial intelligence: * Dreyfus 1972, Dreyfus & Dreyfus 1986 * Crevier 1993, pp. 120–132 * McCorduck 2004, pp. 211–239 * Russell & Norvig 2003, pp. 950–952, Gödel 1951: in this lecture, Kurt Gödel uses the incompleteness theorem to arrive at the following disjunction: (a) the human mind is not a consistent finite machine, or (b) there exist Diophantine equations for which it cannot decide whether solutions exist. Gödel finds (b) implausible, and thus seems to have believed the human mind was not equivalent to a finite machine, i.e., its power exceeded that of any finite machine. He recognized that this was only a conjecture, since one could never disprove (b). Yet he considered the disjunctive conclusion to be a "certain fact". The Mathematical Objection: * Russell & Norvig 2003, p. 949 * McCorduck 2004, pp. 448–449 Making the Mathematical Objection: * Lucas 1961 * Penrose 1989 Refuting Mathematical Objection: * Turing 1950 under "(2) The Mathematical Objection" * Hofstadter 1979 Background: * Gödel 1931, Church 1936, Kleene 1935, Turing 1937 Graham Oppy (20 January 2015). "Gödel's Incompleteness Theorems". Stanford Encyclopedia of Philosophy. Archived from the original on 22 April 2016. Retrieved 27 April 2016. These Gödelian anti-mechanist arguments are, however, problematic, and there is wide consensus that they fail. Stuart J. Russell; Peter Norvig (2010). "26.1.2: Philosophical Foundations/Weak AI: Can Machines Act Intelligently?/The mathematical objection". Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. ISBN 978-0-13-604259-4. even if we grant that computers have limitations on what they can prove, there is no evidence that humans are immune from those limitations. Mark Colyvan. An introduction to the philosophy of mathematics. Cambridge University Press, 2012. From 2.2.2, 'Philosophical significance of Gödel's incompleteness results': "The accepted wisdom (with which I concur) is that the Lucas-Penrose arguments fail." Iphofen, Ron; Kritikos, Mihalis (3 January 2019). "Regulating artificial intelligence and robotics: ethics by design in a digital society". Contemporary Social Science: 1–15. doi:10.1080/21582041.2018.1563803. ISSN 2158-2041. "Ethical AI Learns Human Rights Framework". Voice of America. Archived from the original on 11 November 2019. Retrieved 10 November 2019. Crevier 1993, pp. 132–144. In the early 1970s, Kenneth Colby presented a version of Weizenbaum's ELIZA known as DOCTOR which he promoted as a serious therapeutic tool.[216] Joseph Weizenbaum's critique of AI: * Weizenbaum 1976 * Crevier 1993, pp. 132–144 * McCorduck 2004, pp. 356–373 * Russell & Norvig 2003, p. 961 Weizenbaum (the AI researcher who developed the first chatterbot program, ELIZA) argued in 1976 that the misuse of artificial intelligence has the potential to devalue human life. Wendell Wallach (2010). Moral Machines, Oxford University Press. Wallach, pp 37–54. Wallach, pp 55–73. Wallach, Introduction chapter. Michael Anderson and Susan Leigh Anderson (2011), Machine Ethics, Cambridge University Press. "Machine Ethics". aaai.org. Archived from the original on 29 November 2014. Rubin, Charles (Spring 2003). "Artificial Intelligence and Human Nature". The New Atlantis. 1: 88–100. Archived from the original on 11 June 2012. Brooks, Rodney (10 November 2014). "artificial intelligence is a tool, not a threat". Archived from the original on 12 November 2014. "Stephen Hawking, Elon Musk, and Bill Gates Warn About Artificial Intelligence". Observer. 19 August 2015. Archived from the original on 30 October 2015. Retrieved 30 October 2015. Chalmers, David (1995). "Facing up to the problem of consciousness". Journal of Consciousness Studies. 2 (3): 200–219. Archived from the original on 8 March 2005. Retrieved 11 October 2018. See also this link Archived 8 April 2011 at the Wayback Machine Horst, Steven, (2005) "The Computational Theory of Mind" Archived 11 September 2018 at the Wayback Machine in The Stanford Encyclopedia of Philosophy Searle 1980, p. 1. This version is from Searle (1999), and is also quoted in Dennett 1991, p. 435. Searle's original formulation was "The appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to understand and have other cognitive states." [230] Strong AI is defined similarly by Russell & Norvig (2003, p. 947): "The assertion that machines could possibly act intelligently
AnimeshMondol
# SU19CSE299S02G05 <p align="center"> <img width="200" height="200" src="https://media.licdn.com/dms/image/C560BAQEFJPl7DXD1Dg/company-logo_200_200/0?e=2159024400&v=beta&t=4wzyvb7GBsvMovoet_LGS9uj_Gso_kmfWqCXnqydCDI"> </p> <h1 style="text-align: center">         North South University</h1> #        Project Name: Stop Food Waste **                      CSE299: JUNIOR DESIGN** **                        SEC: 02, Group: 05** **                Instructor:** **SHAIKH SHAWON AREFIN SHIMON (SAS3)** **                      Semester:** **Summer 2019** <br> **                        GROUP MEMBERS**                        1. **Animesh Mondol**                          **ID: 1611971042** **                   Email: animesh.sarkar02@northsouth.edu**                        2. **Shamsunnar Sumi**                          **ID: 1621762042**                    **Email: shamsunnar.sumi@northsouth.edu**           **GitHub Repository Link:** **https://github.com/AnimeshMondol/SU19CSE299S02G05NSU**                       **Date Prepared: 19/06/2019** <br><br><br><br><br> **Project Details:** Our project idea is Stop Food Waste. In our country during different program there are some large amount of food are being wasted. So we want to make a web app where people can donate that food to the poor needy people. With this web app we are trying to solve the problem of food faced by a certain amount of people in our country. We also want to use mobile phone access to the users so that they can use mobile phone to access the web page. **Features:** <br> **Login:** The system provides security features through email-password matching where only authorized user can access the system. **Admin Login:** In this part the manager will keep up the donated elements and donor details. He/ She will be able to know all the information and edit them. He/ She can assign people where to pick up the food from which will be shown in Google Map. 1. Add user 2. Remove user 3. View user 4. View request 5. Remove request 6. View donation 7. Confirm pickup location 8. Logout **User Login:** In this part user will be able to login and he/she will be able to see all the donor and there will be an option where user can be a donor. He/ She can also see the place in the map where to go, to pick up the food. **User Login:** 1. Donate food 2. Sign In 3. Become a donor 4. Send request 5. View request 6. About us 7. Contact us 8. Logout **Donate food:** In this part user can donote food by seeing the request id send by the other user. It will also contain a form where donor needs to add his name, mobile, email, req_id, quntity. By submitting the form it will take it to the user map for setup the location in the map. **Request for food:** In this part user can request for food to the website so that other user(donor) can donote food to them for donotion. **Donote Us** In this part user will have a option to donote us money if they want for the development purpose. In this part there will be Bkash and Rocket no where donors can donate us. It will contain a form where name,mobile,amount and transaction id will be asked to stored on DB. **View requests** Here user can see the pending requests for food. **About Us:** In this section there will be information about the program. **Contact Us** In this part there will be information about how to contact us and also there will be a part where user can poot comments and ask for help directly to the admin. **Technology:** HTML, PHP, CSS, Bootstrap template, My SQL Server, Google Map API. **Business Plan:** It is mainly a free to use for everyone. There will be no need for any amount of money to create an account in this webpage. But through Google AdSense we want to monetize the webpage. Also if any donor wants to donate some amount of money they can do it through Bkash , Rocket . <br><br> **Design:** We used the template of Bootstrap containing all the CSS and JS files downloaded from their website. We don't use any extra design in the webpage. But we used some image files to make the website look a little good. **Planning:** After selecting the project, we started our work by creating a UML diagram to make our work easy and it helped us to understand what we need to add or not in our website. Then we created issues in the project board. Then by weekly submission we tried to solve those issues. The project contains total of 43 closed issues which was used to make this website. All the details are shown in the project bord https://github.com/AnimeshMondol/SU19CSE299S02G05NSU/projects/1 **What did/didn't work:** Around 85-90% of our project run's very well. But we faced some problems. They are: 1. As we were unable to constract the foregin key in the DB after login the user need to input his name, mobile no , email and other informations manually. 2. For the donate us page under user, we didn't find any proper solution on how we can give the user the confermation about if his donation is received or not. So we manually take the name , mobile , the amount of money he donated and transaction id and store in the DB. 3. The admin map has some bugs that we were unable to fix. It doesn't refresh after the pickup confermation was done by the admin. 4. We wanted user to make the pickup request from his/her phone but we didn't able to make the website suitable for phones. **Screenshots:**                         **Image: DB(Foodforall)** <br>                          **Image: Homepage** <br>                          **Image: Login Page** <br>                         **Image: Join us Page** <br>                         **Image: Donor Login Page** <br>                         **Image: Food Donation** <br>                         **Image: User map** <br>                         **Image: Admin Login** <br>                         **Image: Admin Home** <br>                         **Image: Admin map** <br><br><br> **Conclusion:** 1. First of all we learnt how to use Github. It was completely new for us. But we now know how to use it. 2. We learnt about PHP, HTML and How to create DB connection in Mysql to create a project. 3. If we have more time we may be able to make the full project work properly. 4. In future, if we get chance we also want to create a android app for this weabsite. **References:** 1.https://getbootstrap.com/docs/4.3/examples/starter-template/ 2.https://www.w3schools.com/ 3.https://www.youtube.com/ 4.https://stackoverflow.com/questions/22138746/php-form-not-inserting-into-mysql-database 5.https://www.google.com/search?q=html+color+picker&oq=html+&aqs=chrome.0.69i59j69i57j69i60j69i65l2j69i60.3167j0j7&sourceid=chrome&ie=UTF-8 6.https://www.geeksforgeeks.org/ 7.https://www.youtube.com/watch?v=q2VV3-yWupU 8.https://bitbucket.org/webeasystep/markers_manager_php_mysql/src/master/
ShahadShaikh
Problem Statement Introduction So far, in this course, you have learned about the Hadoop Framework, RDBMS design, and Hive Querying. You have understood how to work with an EMR cluster and write optimised queries on Hive. This assignment aims at testing your skills in Hive, and Hadoop concepts learned throughout this course. Similar to Big Data Analysts, you will be required to extract the data, load them into Hive tables, and gather insights from the dataset. Problem Statement With online sales gaining popularity, tech companies are exploring ways to improve their sales by analysing customer behaviour and gaining insights about product trends. Furthermore, the websites make it easier for customers to find the products they require without much scavenging. Needless to say, the role of big data analysts is among the most sought-after job profiles of this decade. Therefore, as part of this assignment, we will be challenging you, as a big data analyst, to extract data and gather insights from a real-life data set of an e-commerce company. In the next video, you will learn the various stages in collecting and processing the e-commerce website data. Play Video2079378 One of the most popular use cases of Big Data is in eCommerce companies such as Amazon or Flipkart. So before we get into the details of the dataset, let us understand how eCommerce companies make use of these concepts to give customers product recommendations. This is done by tracking your clicks on their website and searching for patterns within them. This kind of data is called a clickstream data. Let us understand how it works in detail. The clickstream data contains all the logs as to how you navigated through the website. It also contains other details such as time spent on every page, etc. From this, they make use of data ingesting frameworks such as Apache Kafka or AWS Kinesis in order to store it in frameworks such as Hadoop. From there, machine learning engineers or business analysts use this data to derive valuable insights. In the next video, Kautuk will give you a brief idea on the data that is used in this case study and the kind of analysis you can perform with the same. Play Video2079378 For this assignment, you will be working with a public clickstream dataset of a cosmetics store. Using this dataset, your job is to extract valuable insights which generally data engineers come up within an e-retail company. So now, let us understand the dataset in detail in the next video. Play Video2079378 You will find the data in the link given below. https://e-commerce-events-ml.s3.amazonaws.com/2019-Oct.csv https://e-commerce-events-ml.s3.amazonaws.com/2019-Nov.csv You can find the description of the attributes in the dataset given below. In the next video, you will learn about the various implementation stages involved in this case study. Attribute Description Download Play Video2079378 The implementation phase can be divided into the following parts: Copying the data set into the HDFS: Launch an EMR cluster that utilizes the Hive services, and Move the data from the S3 bucket into the HDFS Creating the database and launching Hive queries on your EMR cluster: Create the structure of your database, Use optimized techniques to run your queries as efficiently as possible Show the improvement of the performance after using optimization on any single query. Run Hive queries to answer the questions given below. Cleaning up Drop your database, and Terminate your cluster You are required to provide answers to the questions given below. Find the total revenue generated due to purchases made in October. Write a query to yield the total sum of purchases per month in a single output. Write a query to find the change in revenue generated due to purchases from October to November. Find distinct categories of products. Categories with null category code can be ignored. Find the total number of products available under each category. Which brand had the maximum sales in October and November combined? Which brands increased their sales from October to November? Your company wants to reward the top 10 users of its website with a Golden Customer plan. Write a query to generate a list of top 10 users who spend the most. Note: To write your queries, please make necessary optimizations, such as selecting the appropriate table format and using partitioned/bucketed tables. You will be awarded marks for enhancing the performance of your queries. Each question should have one query only. Use a 2-node EMR cluster with both the master and core nodes as M4.large. Make sure you terminate the cluster when you are done working with it. Since EMR can only be terminated and cannot be stopped, always have a copy of your queries in a text editor so that you can copy-paste them every time you launch a new cluster. Do not leave PuTTY idle for so long. Do some activity like pressing the space bar at regular intervals. If the terminal becomes inactive, you don't have to start a new cluster. You can reconnect to the master node by opening the puTTY terminal again, giving the host address and loading .ppk key file. For your information, if you are using emr-6.x release, certain queries might take a longer time, we would suggest you use emr-5.29.0 release for this case study. There are different options for storing the data in an EMR cluster. You can briefly explore them in this link. In your previous module on hive querying, you copied the data to the local file system, i.e., to the master node's file system and performed the queries. Since the size of the dataset is large here in this case study, it is a good practice to load the data into the HDFS and not into the local file system. You can revisit the segment on 'Working with HDFS' from the earlier module on 'Introduction to Big data and Cloud'. You may have to use CSVSerde with the default properties value for loading the dataset into a Hive table. You can refer to this link for more details on using CSVSerde. Also, you may want to skip the column names from getting inserted into the Hive table. You can refer to this link on how to skip the headers.
AryamanTewari
FlyAway (An Airline Booking Portal). Project 2 DESCRIPTION Project objective: As a Full Stack Developer, design and develop an airline booking portal named as FlyAway. Use the GitHub repository to manage the project artifacts. Background of the problem statement: FlyAway is a ticket-booking portal that lets people book flights on their website. The website needs to have the following features: ● A search form in the homepage to allow entry of travel details, like the date of travel, source, destination, and the number of persons. ● Based on the travel details entered, it will show the available flights with their ticket prices. ● Once a person selects a flight to book, they will be taken to a register page where they must fill in their personal details. In the next page, they are shown the flight details of the flight that they are booking, and the payment is done via a dummy payment gateway. On completion of the payment, they are shown a confirmation page with the details of the booking. For the above features to work, there will be an admin backend with the following features: ● An admin login page where the admin can change the password after login, if he wishes ● A master list of places for source and destination ● A master list of airlines ● A list of flights where each flight has a source, destination, airline, and ticket price The goal of the company is to deliver a high-end quality product as early as possible. The flow and features of the application: ● Plan more than two sprints to complete the application ● Document the flow of the application and prepare a flow chart ● List the core concepts and algorithms being used to complete this application ● Implement the appropriate concepts, such as exceptions, collections, and sorting techniques for source code optimization and increased performance You must use the following: ● Eclipse/IntelliJ: An IDE to code for the application ● Java: A programming language to develop the web pages, databases, and others ● SQL: To create tables for admin, airlines, and other specifics ● Maven: To create a web-enabled Maven project ● Git: To connect and push files from the local system to GitHub ● GitHub: To store the application code and track its versions ● Scrum: An efficient agile framework to deliver the product incrementally ● Search and Sort techniques: Data structures used for the project ● Specification document: Any open-source document or Google Docs The following requirements should be met: ● The source code should be pushed to your GitHub repository. You need to document the steps and write the algorithms in it. ● The submission of your GitHub repository link is mandatory. In order to track your task, you need to share the link of the repository. You can add a section in your document. ● Document the step-by-step process starting from sprint planning to the product release. ● The application should not close, exit, or throw an exception if the user specifies an invalid input. ● You need to submit the final specification document which will include: ● Project and developer details ● Sprints planned and the tasks achieved in them ● Algorithms and flowcharts of the application ● Core concepts used in the project ● Links to the GitHub repository to verify the project completion
ronykader
Wallet Master is an API-based Financial Management System built with Laravel 11, designed for managing users, roles, organizations, accounts, transactions, budgets, family members, and subscription plans.
MunadEAli
Designed and developed a teleoperation system for a modified SCARA robot using an intelligent virtual environment, featuring trajectory planning, image processing feedback, and Master-Slave control architecture for precise IC handling
Superman/woman - Programming Guru Needed! http://careers.interfacefinancial.com We need a Super Hero! It really does depend on your definition, though. If you are into great people, a startup mentality with no startup issues and you enjoy writing code using Python and C# or C++ in a Linux environment, then you'll love working at IFG! Join the company that’s bringing technological advancement to the commercial finance industry! We're looking for a Software Engineer to join our awesome development team. We like working with nice people who are excited to learn. :) Here's what we need... Software Architect/Financial Engineer The Role Financial Engineer/Software Data Architect is responsible for the strategic architecture and deployment of the data infrastructure ecosystems. As a key member of the technology team you will be responsible for architecting, designing and developing major components of a next generation stream and batch processing lending platform. Qualifications *Strong experience with object-oriented design, coding and testing patterns *Experience in architecting, building and maintaining (commercial or open source) software platforms and large-scale data infrastructures *Experience building big data solution *2+ years software development experience *Experience with other technology such as Amazon EC2 is a plus *A strong team player, ability to quickly triage and troubleshoot complex problems Responsibilities and Duties: *Develop and execute various methods for data collection and acquisition. *Analyze statistics, recommend ways to improve various outlining risk model. *Develop and write various functional requirement documents to assist various software developers. *Coordinate with various software developers and perform various tests on software requirements. *Administer technical performance and monitor up gradation process for various businesses. *Monitor all account related issues and provide expert advice on various methods and processes for existing systems. *Perform and evaluate all functional requirements and perform required calculations such as algorithms. *Perform research on various products, gather knowledge on user requirement and develop plans to improve products. *Design and execute various pricing models for financial products and services. *Monitor all lending models, establish capacity parameters and recommend improvements on same. *Administer all risk calculations for customer and evaluate appropriate tools for same. *Manage and resolve all complex financial issues and develop effective mathematical and statistical methods to resolve issues. *Coordinate with software developers and develop effective implementation methods for various functional products. Preferred skills: *Numerical/financial algorithms, XML, JSON, C#, Java *Database relationship and data schemas *RESTFUL API knowledge *Software testing methodology *financial analysis skills *FRM (Financial Risk Manager) Certification Education *Bachelor's Degree required *Master Degree preferred 2 positions open Salary: $90K-$100K
ApalaSandeepReddy
DESCRIPTION Project objective: As a Full Stack Developer, design and develop a backend administrative portal for the Learner’s Academy. Use the GitHub repository to manage the project artifacts. Background of the problem statement: Learner’s Academy is a school that has an online management system. The system keeps track of its classes, subjects, students, and teachers. It has a back-office application with a single administrator login. The administrator can: ● Set up a master list of all the subjects for all the classes ● Set up a master list of all the teachers ● Set up a master list of all the classes ● Assign classes for subjects from the master list ● Assign teachers to a class for a subject (A teacher can be assigned to different classes for different subjects) ● Get a master list of students (Each student must be assigned to a single class) There will be an option to view a Class Report which will show all the information about the class, such as the list of students, subjects, and teachers The goal of the company is to deliver a high-end quality product as early as possible. The flow and features of the application: ● Plan more than two sprints to complete the application ● Document the flow of the application and prepare a flow chart ● List the core concepts and algorithms being used to complete this application ● Implement the appropriate concepts, such as exceptions, collections, and sorting techniques for source code optimization and increased performance You must use the following: ● Eclipse/IntelliJ: An IDE to code for the application ● Java: A programming language to develop the web pages, databases, and others ● SQL: To create tables for admin, classes, students, and other specifics ● Git: To connect and push files from the local system to GitHub ● GitHub: To store the application code and track its versions ● Scrum: An efficient agile framework to deliver the product incrementally ● Search and Sort techniques: Data structures used for the project ● Specification document: Any open-source document or Google Docs The following requirements should be met: ● The source code should be pushed to your GitHub repository. You need to document the steps and write the algorithms in it. ● The submission of your GitHub repository link is mandatory. In order to track your task, you need to share the link of the repository. You can add a section in your document. ● Document the process step-by-step starting from sprint planning to the product release. ● The application should not close, exit, or throw an exception if the user specifies an invalid input. ● You need to submit the final specification document which will include: ● Project and developer details ● Sprints planned and the tasks achieved in them ● Algorithms and flowcharts of the application ● Core concepts used in the project ● Links to the GitHub repository to verify the project completion
Best Web Designing Graphic And Digital Marketing Institute In Chandigarh Visual Media Academy is a WEB DESGNING, GRAPHIC ,AND DIGITAL MARKETING Training Institute which provides Professional training in Digital Marketing. The Prime Objective of Visual Media Academy is to Promote Digital Marketing and Train the Students in this Field, Who wants to succeed in a Career in Digital Marketing. What do They offer? Master WEB DESIGNING Skills Including GRAPHIC DESIGNING and DIGITAL MARKETING Personalized Attention by Our Experts. Participation in Live Projects. What doThey do? They addressing the global shortage of digital skills by giving you Digital Marketing Education. We Deliver Education programmes in classroom, online, and through licensed partners.Transform yourself into an expert digital marketer and become industry-ready by mastering the latest tools on top domains like SEO, social media Marketing and more. Build and execute your future into successful campaigns for real industry projects sponsored by the top companies. Track your digital marketing route and journey with the guaranteed opportunities by our placement cell. What is DESIGNING? So, Basically A design is a plan or specification for the construction of an object or system or for the implementation of an activity or process, or the result of that plan or specification in the form of a prototype, product or process. The verb to design expresses the process of developing a design. In some cases, the direct construction of an object without an explicit prior plan (such as in craftwork, some engineering, coding, and graphic design) may also be considered to be a design activity. The design usually has to satisfy certain goals and constraints, may take into account aesthetic, functional, economic, or socio-political considerations, and is expected to interact with a certain environment. Major examples of designs include architectural blueprints, engineering drawings, business processes, circuit diagrams, and sewing patterns Types of Courses they Provide Web Designing Graphic Designin Digital Marketing Motion Graphics And More. Web Designing:-Web design refers to the design of websites that are displayed on the internet. It usually refers to the user experience aspects of website development rather than software development. ... A web designer works on the appearance, layout, and, in some cases, content of a website. Graphic Designing:-Graphic design is a craft where professionals create visual content to communicate messages. By applying visual hierarchy and page layout techniques, designers use typography and pictures to meet users’ specific needs and focus on the logic of displaying elements in interactive designs, to optimize the user experience. Digital Marketing:-At a high level, digital marketing refers to advertising delivered through digital channels such as search engines, websites, social media, email, and mobile apps. Using these online media channels, digital marketing is the method by which companies endorse goods, services, and brands. Consumers heavily rely on digital means to research products. For example, Think with Google marketing insights found that 48% of consumers start their inquiries on search engines, while 33% look to brand websites and 26% search within mobile applications. Motion Graphics:- Motion graphics (sometimes mograph) are pieces of animation or digital footage which create the illusion of motion or rotation, and are usually combined with audio for use in multimedia projects. ... Motion graphics are exceptional way to communicate with viewer, and it can add depth to the story. What skills will you gain? Meaning and understanding of web and graphic Designing And digital marketing :- Acquire the right marketing skills, become an industry expert and grow your career Soft Skills Modules:- 1. Business communication 2. Presentation skills knowledge of Tools:- Learn Different Digital Marketing tools for Creating Content- Google Analytics , Google Keyword Planner, Google Search Etc. Get Certified and improve your career opportunities Visual Media Academy certificates are the most reliable way to make an entry into any industry and get a headstart in finding the most relevant jobs at some of the top companies in the world. WHY CHOOSE them ? Well Experienced trainer from digital marketing Field 100% Job Assistence Weekend batch SEO Course as per Latest market trends Personalized attention to each Candidate Internship Programs for Fresher . Hurry up and enroll now
Python is point of fact the Next Big Thing to investigate. There is no need to be worried about its worth, profession possibilities, or accessible positions. Python's commitment to the advancement of your calling is huge, as its notoriety among designers and different areas is step by step waning. Python is "the one" for an assortment of reasons. It's a straightforward pre-arranged language that is not difficult to get. Subsequently, the general improvement time for the task code is diminished. It accompanies an assortment of structures and APIs that assistance with information examination, perception, and control. Employment opportunities in Python While India has a critical interest for Python engineers, the stock is very restricted. We'll utilize a HR master articulation to validate this. For both Java and Python, the expert was relied upon to employ ten developers. For Java, they got over 100 fantastic resumes, however just eight for Python. In this way, while they needed to go through an extensive method to get rid of resilient people, they had no real option except to acknowledge those eight individuals with Python. What does this say about the circumstance to you? Regardless of Python's straightforward language structure, we desperately need more individuals in India to update their abilities. This is the reason learning Python is a particularly colossal opportunity for Indians. With regards to work openings, there may not be numerous for Python in India. Notwithstanding, we have countless assignments accessible per Python developer. In the relatively recent past, one of India's unicorn programming organizations was stood up to with an issue. It had gotten a $200 million (Rs. 1200 crore) arrangement to develop an application store for a significant US bank. Be that as it may, the organization required talented Python developers. Since Python was the best language for the undertaking, it wound up paying a gathering of independent Python developers in the United States multiple times the charging sum. For sure and Naukri, for instance, have 20,000 to 50,000 Python work postings, showing that Python vocation openings in India are copious. It is an insightful choice to seek after a profession in Python. The diagrams underneath show the absolute number of occupation advertisements for the most well known programming dialects. Python Job Descriptions Anyway, what sorts of work would you be able to get in the event that you know Python? Python's degree is broad in information science and investigation, first off. Customers regularly demand that secret examples be separated from their informational indexes. In AI and man-made reasoning, it is additionally suggested. Python is a top choice among information researchers. Furthermore, we figured out how Python is used in web advancement, work area applications, information examination, and organization programming in our article on Python applications. Python Job Profiles With Python on your resume, you might wind up with one of the accompanying situations in a presumed organization: 1. Programmer Investigate client necessities Compose and test code Compose functional documentation Counsel customers and work intimately with other staff Foster existing projects 2. Senior Software Engineer Foster excellent programming engineering Mechanize assignments by means of prearranging and different apparatuses Survey and troubleshoot code Perform approval and confirmation testing Carry out form control and configuration designs 3. DevOps Engineer Send refreshes and fixes Break down and resolve specialized issues Plan systems for support and investigating Foster contents to mechanize representation Convey Level 2 specialized help 4. Information Scientist Recognize information sources and mechanize the assortment Preprocess information and dissect it to find patterns Plan prescient models and ML calculations Perform information representation Propose answers for business challenges 5. Senior Data Scientist Manage junior information experts Construct logical devices to create knowledge, find designs, and foresee conduct Execute ML and measurements based calculations Propose thoughts for utilizing had information Impart discoveries to colleagues While many significant firms are as yet utilizing Java, Python is a more seasoned yet at the same time well known innovation. Python's future is splendid, on account of: 1.Artificial Intelligence (AI): Machine knowledge is alluded to as man-made consciousness. This is as a conspicuous difference to the regular astuteness that people and different creatures have. It is one of the most up to date advances that is clearing the globe. With regards to AI, Python is one of the main dialects that rings a bell; truth be told, it is probably the most ideally equipped language for the work. We have different structures, libraries, and devices devoted to permitting AI to swap human work for this objective. It supports this, however it additionally further develops productivity and precision. Discourse acknowledgment frameworks, self-driving vehicles, and other AI-based advancements are models. The accompanying devices and libraries transport for these parts of AI: AI – PyML, PyBrain, scikit-learn, MDP Toolkit, GraphLab Create, MIPy General AI – pyDatalog, AIMA, EasyAI, SimpleAI Neural Networks – PyAnn, pyrenn, ffnet, neurolab Normal Language and Text Processing – Quepy, NLTK, genism 2. Enormous Data Enormous Data is the term for informational collections so voluminous and complex that conventional information handling application programming is insufficient in managing them. Python has assisted Big Data with developing, its libraries permit us to break down and work with a lot of information across groups: Pandas scikit-learn NumPy SciPy GraphLab Create IPython Bokeh Agate PySpark Dask 3. Systems administration Python additionally allows us to design switches and switches, and perform other organization mechanization undertakings cost-viably. For this, we have the accompanying Python libraries: Ansible Netmiko NAPALM(Network Automation and Programmability Abstraction Layer with Multivendor Support) Pyeapi JunosPyEZ PySNM Paramiko SSH Python Course
nirmitkotadiya
A comprehensive 30-day structured learning plan for software engineers to master System Design and Microservices Architecture. From fundamentals to advanced concepts with daily topics, hands-on exercises, case studies, and architectural diagrams. Perfect for interview preparation and career growth.
Saicharan-Banothu
I am enrolled in an agentic AI course, mastering the design of autonomous systems. I'm learning to build AI agents that can reason, plan, and execute complex tasks independently, moving beyond simple prediction. This program is bridging advanced AI theory with practical, real-world applications for creating sophisticated, goal-driven models.
99websitedesign
We design ideas and drive growth As a multidimensional digital marketing company in Melbourne with more than 5 years of industry experience, we analyse and understand the developing digital world. We consider any website as a human interactive layout that connects with your emotions and helps in generating revenue, from influencing users to fulfil their needs through the wallet which we call them as potential buyers. The experts at 99 Website Design Agency identify the motive behind the website and develop custom web design by putting ourselves into the customer’s shoes. Added to our global recognizing website design services we have a complete digital package such as SEO, Google Ads and so on which helps our client to come up in Google ranking. We guarantee a result driven bond between us for which you will not feel lost at any time. Services Website Design Your website is the #1 Asset for the marketing We at 99 Website Design Agency who was known for the best Website design company in Melbourne are packed with industry experts just for you. Well your website is the first thing that a person will visit and it has to be so attractive and relatable that the person will love to navigate within. That makes your website an important asset for you and you win the customer’s heart at the first step itself. Thanks to our creative team who will make this happen for you. It's additionally what goes on behind the front end of the website that is significant – how effectively is it optimized for SEO? How well is it designed with the customer in mind? How smooth is the end user website journey? These are immeasurably significant parts of a great website and will impact how well it converts visitors into potential buyers. The optimized and simplified web design process of 99 Website Design Agency makes us stand out of the crowd. The web design process measure begins with fostering an appropriate task plan and project timetable. Right after the initial step, we direct competitor analysis and market research along with trend analysis. As the website design steps go on we start with the sitemap and wireframe structure of the website. When the key features and multi functionalities are organized appropriately, we place the substance and finish the cycle by UX/UI plan for boosting the customer interaction. Google ads We at 99 Website Design Agency consider Google Ads a default advertising system. Everything's tied in with claiming however much land in Google list items as could reasonably be expected – both paid and organic postings. In the context of Google Ads, considering precisely what your target audience is looking for will assist with guaranteeing that your business shows up in one of the top 4 paid positions (regardless of whether your site isn't ranking for those terms at this point). The reality is your rivals are there, so you should be there as well. We have curated 4 essential strategies for your Google Ads campaign - Search Strategy is the key player: The utmost step to any success milestone is Google Ads is having the right system set up at the right place for the right audience. Campaign flowchart and ready to launch: Then it comes to structure your ad campaign which includes a stunning landing page, value proposition, a great CTA and of course a core messaging which will make them stop at the campaign page. Tracking, Reporting and optimization: This is regarding how we intake more data and perceive what's working and what's not working. To do that, it is very important to reach a wide range of audience at the earliest. This will help us to revise and publish our campaign so as to get a good result. The Campaign is a channel: and so on the Google ad campaign becomes a channel so that you can scale up and down so easily without any problem and that is the beauty of the campaign. Search Engine Optimisation SEO is the effective way of increasing the volume of traffic to your website by organic method, which means you don't have to pay for the traffic. Well this is not just that easy to put into action. Apart from regular strategies there are a lot of hidden techniques and secret pipelines to implement for a quick and long term result which make us the best SEO agency in Australia. Thanks to our brain masters behind the SEO team who will make this happen for you. Our 4 Result Driven strategies for a successful SEO campaign SEO Audit and Technical- With regards to SEO, our SEO Audit is an intensive review of your current technical SEO arrangement and how your website is right now performing. It gives clear bits of knowledge into enhancements that can be carried out for better results. This includes Image alt tags, robot.txt, www to non-www redirection which may affect your backlinks pointing to two different addresses. Keyword Research and Content Creation- The most important aspect of SEO starts here – developing rich, relevant, engaging and current content. It rolls around what your target customer is searching for and 99 Website Design Agency is highly enriched in keyword research and a unique content creation. By continually developing new and evolving content you can apply it to update your website and look out to other different websites, too. Backlinks are our ultimate goal- External Links to your website is a superb way to not just direct people to your site, they assist you with ranking better and higher. They tell Google you're an expert on a specific subject so the more great quality backlinks your website gets, the more trust and authority the website builds. We plan for long term result- Incorporating a successful SEO campaign is about sticking to the top pages for a long period and evolving with fresh and updated content to reach a wide range of traffic on a target audience set up.Our experts will look after it on a regular basis just to ensure that your website never goes out of trend. Why is 99 Website Design Agency the right choice for you? We have optimized and ranked our website in top page of search engines and we beat the competitors for a long time. If we can rank our website, we can do it for you as well. We are one of its kinds who do care for your website even after it works successfully. We timely measure and improve its quality so that it works even better. We have a dedicated team to look after our clients queries and help them till they get full satisfaction. We are even open to step by step training sessions if you are a complete new to this field. Not the least, We take care of your budget. Our result oriented team is more inclined towards the result first. Last year 99 Website Design Agency was rated higher with the most Digital Marketing Company in Australia. Thanks!
AlessandroFurina
This repository contains a summary of the projects developed during the master degree in Robotics and Automation Engineering. These regard control design, path planning algorithm, embedded system programming, mobile robotics.
master two fundamental agentic design patterns that power modern AI workflows. You'll build a parallel meal planning system that coordinates multiple AI chefs, and an iterative investment advisor that refines recommendations through continuous feedback loops.
Bryscar20
Sunflower Masters IMS is a platform designed to efficiently track, manage, and optimize our sunflower inventory. Here are some key functionalities typically offered by our systems: Inventory Tracking, Order Management, Stock replenishment, reporting and analytics, Forecasting and Demand Planning etc
cherryinstitute12345
SP3D Training Institute in Marathahalli. Online Piping.com provide SP3d Training since 2014. still, now we trained more than 2000+ Sp3d Designers. Smart 3D ensures design accuracy and consistency through the enforcement of design rules. Smart 3D reduces design errors, minimizes engineering changes, and cuts down on rework. Design rule enforcement increases project quality and reliability by enabling faster and more efficient creation, transfer, and review of design iterations. All project participants can make informed and timely decisions throughout the project. Smart 3D provides tools for the continuous monitoring of design rules and notification of the impacts of change throughout a project’s design phase. Over the years, Croma Campus has been considered the best provider of SP3D online training in India, we help learners to master all SP3D fundamental concepts that comprise basics, principles, style rules, piping hierarchy, solid modeling, grid system, coordinate system, handrails, etc. The training has been planned under the guidance of an expert team with advanced course content and the syllabus. Once you complete the training with us, you could achieve your career goals and establish yourself as an impeccable source in the IT industry. The SP3D online training is suitable for both fresher and experienced professionals. You could join weekend, weekdays, or fast track batches, as per the requirement. Our SP3D placement course helps you to acquire all the vital skills and establish yourself as an expert SP3D administrator in the industry. if you are interested pls contact us +918296698585 https://www.cherryinstitute.in/
cherryinstitute12345
ETABS Training Institute in Marathahalli. ETABS is a highly efficient analysis and design program developed especially for building systems. It is loaded with an integrated system with an ability to handle the largest and most complex building models and configurations. The course aims to offer comprehensive knowledge on the ETABS software and its applications. The course will help the candidates to acquire in-depth details about the different procedures and simplified analysis aspects of the design models. The certification converts a candidate into an expert that is ready to work in the civil design industry. ETABS Training in Noida by CETPA is designed to help the fresher as well as experienced Civil Engineers (Masters/Degree/Diploma) and architect who are engaged in multi-story building analysis and designing and it is also appropriate for those who work for various range of applications related to mathematical model analysis of buildings such as interior design, architectural, landscape architecture etc. It is the best ETABS training institute. ETABS Software Training Course at CETPA provides theory classes along with placing complete focus on practical sessions so that students get the deep understanding of the concepts. Students in CETPA get trained from skilled and experienced experts who have sound knowledge of the concepts. CETPA provide friendly environment between trainers and students and along with that, individual attention is given to each student. ETABS is a coordinated programming package for the structural analysis and plan of structures. ETABS offers 3D object based demonstrating and visualization apparatuses, straight and nonlinear analytical power, plan capacities for a wide scope of materials, and realistic showcases, reports, and schematic drawings that permit clients to rapidly and effectively get examination and design results. If you are interested for demo 8296698585 https://www.cherryinstitute.in/
cherryinstitute12345
ETABS Training Institute in Marathahalli. ETABS is a highly efficient analysis and design program developed especially for building systems. It is loaded with an integrated system with an ability to handle the largest and most complex building models and configurations. The course aims to offer comprehensive knowledge on the ETABS software and its applications. The course will help the candidates to acquire in-depth details about the different procedures and simplified analysis aspects of the design models. The certification converts a candidate into an expert that is ready to work in the civil design industry. ETABS Training in Noida by CETPA is designed to help the fresher as well as experienced Civil Engineers (Masters/Degree/Diploma) and architect who are engaged in multi-story building analysis and designing and it is also appropriate for those who work for various range of applications related to mathematical model analysis of buildings such as interior design, architectural, landscape architecture etc. It is the best ETABS training institute. ETABS Software Training Course at CETPA provides theory classes along with placing complete focus on practical sessions so that students get the deep understanding of the concepts. Students in CETPA get trained from skilled and experienced experts who have sound knowledge of the concepts. CETPA provide friendly environment between trainers and students and along with that, individual attention is given to each student. ETABS is a coordinated programming package for the structural analysis and plan of structures. ETABS offers 3D object based demonstrating and visualization apparatuses, straight and nonlinear analytical power, plan capacities for a wide scope of materials, and realistic showcases, reports, and schematic drawings that permit clients to rapidly and effectively get examination and design results. If you are interested for demo 8296698585 https://www.cherryinstitute.in/
aravindratna93
as per the evolution in GIS now-a-days there are many advancements using advanced web technologies to implement various applications such as updating a city master plan so as to reduce the manual efforts. This paper describes completely how an Open Source GIS system is designed interactively to reach the obligations for the common man using all the Open Source tools required. Geoserver and Google Maps API V3 are being used to develop and deploy in this project. Keyhole Markup Language (KML) files are created according to the user’s data regarding the locations and its attributes. Here Google Maps API acts as a shape file or as a base on which these KML files are hence applied to categorize the user data such as various wards, hospitals, schools, restaurants etc. in a particular city.
AUTO CAD Training Institute in Marathahalli. CAD course helps students to acquire knowledge about drafting civil projects and acquaint them with a set of drawings which include planning, profile cross-sections, topographic maps, and subdivisions. It also trains candidates to use CAD software in Building Information modeling (BIM) for augmenting Civil Engineering Designs and Construction Documentation. AutoCAD Electrical is used by electrical engineers for designing circuit drawings, electrical panels, Wiring System, Control Panels and Programmable logical Controllers I/O Designs. There are many other features which make this software popular among electrical engineers for designing. In an Electrical CAD software the symbols in the diagrams can be intelligent. This means that they can contain an article number for the component they represent and even more important: the electrical connection points of the components can be identified and handled intelligent by the software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. The course is deliberately designed to be a practical representation of the practical experience of the authors. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. Participants will be able to understand the reason for each design step. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. If you are interested for demo pls contact us +91 8296698585 http://cadtrainingbangalore.in/
AUTO CAD Training Institute in Marathahalli. CAD course helps students to acquire knowledge about drafting civil projects and acquaint them with a set of drawings which include planning, profile cross-sections, topographic maps, and subdivisions. It also trains candidates to use CAD software in Building Information modeling (BIM) for augmenting Civil Engineering Designs and Construction Documentation. AutoCAD Electrical is used by electrical engineers for designing circuit drawings, electrical panels, Wiring System, Control Panels and Programmable logical Controllers I/O Designs. There are many other features which make this software popular among electrical engineers for designing. In an Electrical CAD software the symbols in the diagrams can be intelligent. This means that they can contain an article number for the component they represent and even more important: the electrical connection points of the components can be identified and handled intelligent by the software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. The course is deliberately designed to be a practical representation of the practical experience of the authors. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. Participants will be able to understand the reason for each design step. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. If you are interested for demo pls contact us +91 8296698585 http://cadtrainingbangalore.in/
AUTO CAD Training Institute in Marathahalli. CAD course helps students to acquire knowledge about drafting civil projects and acquaint them with a set of drawings which include planning, profile cross-sections, topographic maps, and subdivisions. It also trains candidates to use CAD software in Building Information modeling (BIM) for augmenting Civil Engineering Designs and Construction Documentation. AutoCAD Electrical is used by electrical engineers for designing circuit drawings, electrical panels, Wiring System, Control Panels and Programmable logical Controllers I/O Designs. There are many other features which make this software popular among electrical engineers for designing. In an Electrical CAD software the symbols in the diagrams can be intelligent. This means that they can contain an article number for the component they represent and even more important: the electrical connection points of the components can be identified and handled intelligent by the software. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. Participants will be able to understand the reason for each design step. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. If you are interested for demo pls contact us +91 8296698585 http://cadtrainingbangalore.in/
AUTO CAD Training Institute in Marathahalli. CAD course helps students to acquire knowledge about drafting civil projects and acquaint them with a set of drawings which include planning, profile cross-sections, topographic maps, and subdivisions. It also trains candidates to use CAD software in Building Information modeling (BIM) for augmenting Civil Engineering Designs and Construction Documentation. AutoCAD Electrical is used by electrical engineers for designing circuit drawings, electrical panels, Wiring System, Control Panels and Programmable logical Controllers I/O Designs. There are many other features which make this software popular among electrical engineers for designing. In an Electrical CAD software the symbols in the diagrams can be intelligent. This means that they can contain an article number for the component they represent and even more important: the electrical connection points of the components can be identified and handled intelligent by the software. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. Participants will be able to understand the reason for each design step. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. If you are interested for demo pls contact us +91 8296698585 http://cadtrainingbangalore.in/
AUTO CAD Training Institute in Marathahalli. CAD course helps students to acquire knowledge about drafting civil projects and acquaint them with a set of drawings which include planning, profile cross-sections, topographic maps, and subdivisions. It also trains candidates to use CAD software in Building Information modeling (BIM) for augmenting Civil Engineering Designs and Construction Documentation. AutoCAD Electrical is used by electrical engineers for designing circuit drawings, electrical panels, Wiring System, Control Panels and Programmable logical Controllers I/O Designs. There are many other features which make this software popular among electrical engineers for designing. In an Electrical CAD software the symbols in the diagrams can be intelligent. This means that they can contain an article number for the component they represent and even more important: the electrical connection points of the components can be identified and handled intelligent by the software. In addition to CAD software, students need to learn Geometric Dimensioning and Tolerancing (GDT) concepts for technical communication, and Project Management Principles, and Project Management software. CAD Centre assists students in attaining the knowledge of the unique combination of CAD/BIM software and concept of projects management and building design. The course packages include. Participants will be able to understand the reason for each design step. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. At CADD Centre, we work out the right combination of software & concepts and offer you course packages (Diploma, Professional, and Master Diploma courses) that meet the requirements of the industry. If you are interested for demo pls contact us +91 8296698585 http://cadtrainingbangalore.in/
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