code for Data Science From Scratch book

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

Repo for the data science salary prediction of the Data Science Project From Scratch video on my youtube

MIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: introtodeeplearning-staff@mit.edu Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning

Starting a 100 Days Code Challenge for Learning Data Science from Scratch

Data science for beginners involves learning to extract insights from data using statistics, programming (Python/R), and visualization. Key steps include data collection, cleaning, analysis, modeling, and communicating findings. Beginners should start with Python, basic math (linear algebra/calculus), and build projects to create a portfolio.

A static educational website related to Data Science built using HTML, CSS, JS, Bootstrap and Tailwind from scratch

Gabarit : kickstart your data science project from scratch

All the course materials for the "Stats from Scratch" stream of our Data Science course

Computer science data structures and algorithms implementation from scratch

Notebooks em português criados a partir do livro "Data Science From Scratch" do Joel Grus, 2nd Edition.

Implementation of various data science techniques and research papers

Building a portfolio website from scratch to showcase my data science projects

Examples and hacks inspired by the book Data Science from Scratch by Joel Grus

Code Companion to Joel Grus' book

A comprehensive collection of course materials for learning full-stack data science and machine learning, covering Python, SQL, web development, and ML algorithms. Includes tutorials, datasets, and projects to build end-to-end data-driven applications from scratch.

A comprehensive collection of 180 curated project ideas across 6 technology domains (Backend, Frontend, Data Science, Data Engineering, DevOps, System Design) at 3 difficulty levels. Detailed learning guides help developers master new technologies and build portfolio-ready skills from scratch through hands-on practice.

Mastering Python from Scratch for Data Science & Data Analysis

data-science-from-scratch of joelgrus

We have come a long way since I was a child in the 1960s when all I wanted for Christmas was a slinky and some Rock’Em – Sock’Em Robots. Now imagine we have traveled ten years into the future, and it is Christmas 2031. Alexa has replaced kids’ parents and Santa Claus. Every toy is connected to the Internet and looks like a robot version of the animal it represents. Clean thermonuclear Christmas trees will be providing us with radiant, gamma-ray energy for all our holiday needs. Pogo sticks have also made a comeback, but they are solar-powered and can leap entire city blocks. And while I am busy pretending to be the Ghost of Christmas Future, I thought it would also be fun to ask the Office of the CTO team about their predictions for futuristic, technical toys. So, I posed these two questions: What cool TECHNICAL toy or gadget would you like Santa to bring you this year in 2021? As a participating member of the Office of the CTO, what cool TECHNICAL toy or gadget (that has not yet been invented) would you like Santa to bring you in 10 years from now in 2031? christmas wishlist for the octo team overlay You know what? We just might see I see a sneak preview of some of these magical tech toys of the future in just a few weeks at the CES 2022 conference. In the meantime, take a look at the wish list from all of our Extreme technical gurus: Marcus Burton – Wireless and Cloud Architect Christmas Wish 2021: Is a Tesla Cybertruck an option? I’ll even take a prototype. That will scratch several technology itches at the same time. Think about it…EV, autonomous driving, AI, 5G probably, cloud-connected, mobile-first, and all the best in materials sciences and mechanical engineering applied to trucks. What more could an outdoorsy tech guy want? Christmas Wish 2031: I’m kinda thinking that while everyone else has their brain slurped out in the metaverse (with VR!), I will prefer to go to the actual mountains. But you know, I have a wife and kids, so I have to think about safety. So here’s my wish: a smart personal device that has a full week of battery life (using ultra-thin silicon wafers) with rapid solar charging, LEO satellite connectivity (for sending “eat your heart out” 3D pics to my friends from the “there’s no 6G here” wilderness), and ultra-HD terrain feature maps for modern navigation. Carla Guzzetti – VP, Experience, Messaging & Enablement Christmas Wish 2021: I want this: Meeting Owl Pro – 360-Degree, 1080p HD Smart Video Conference Camera, Microphone, and Speaker Christmas Wish 2031: I want a gadget where we can have virtual meetings without the need for a wearable! Who wants to wear heavy goggles all day? Doug McDonald – Director of Product Management Christmas Wish 2021: As a technologist often looking for a balance between screen time and health and fitness I hope Santa brings me the Aura Strap. The Aura strap adds additional IoT sensory capabilities to compliment your Apple smartwatch. Bioelectrical impedance analysis is the cutting-edge science behind the AURA Strap. This innovation provides a way to truly see how your body changes over the course of a day. Their body composition analysis includes fat, muscle mass, minerals, and hydration; providing personalized insights that improve the results of your workouts, diet, and your lifestyle as a whole. Christmas Wish 2031: Hopefully, this innovation will be here sooner. Still, in the spirit of my first wish from Santa, I also hope to have a service engine warning light for me. The concept is utilizing advancements in biomedical sensory devices to pinpoint potential changes in your physical metrics that may help in seeking medical attention sooner than later if variances in health data occur. I spoke about this concept in the Digital Diagnosis episode of the Inflection Points podcast from the Office of the CTO. Ed Koehler – Principal Engineer Christmas Wish 2021: My answers are short and sweet. I want a nice drone with high-resolution pan, tilt, and zoom (PTZ) cameras. Christmas Wish 2031: In ten years, I want a drone that I can sit inside and fly away! Puneet Sehgal – Business Initiatives Program Manager Christmas Wish 2021: I have always wanted to enjoy the world from a bird’s eye view. Therefore, my wish is for Santa to bring me a good-quality drone camera this year. It is amazing how quickly drones have evolved from commercial /military use to becoming a personal gadget. Christmas Wish 2031: In 2031, I wish Santa could get me a virtual reality (VR) trainer to help me internalize physical motion by looking at a simulation video while sending an electrical impulse to mimic it. It will open endless possibilities, and I could become an ice skater, a karate expert, or a pianist – all in one. Maybe similar research is already being done, but we are far away from something like this maturing for practical use. So, who knows – it’s Santa after all and we are talking 2031! Tim Harrison – Director of Product Marketing, Service Provider Christmas Wish 2021: This year, I would love to extend my audio recording setup and move from a digital 24 channel mixer to a control surface that integrates with my DAW (digital audio workstation) and allows me to use my outboard microphone pre-amps. I’ve been looking at an ICON QCon Pro G2 plus one QCon EX G2 extender to give me direct control over 16 channels at once (I use 16 channels just for my drum kit). Christmas Wish 2031: Ten years from now, I sincerely hope to receive an anti-gravity platform. First, I’ll be old, and climbing stairs will have become more challenging for these creaky old bones. Secondly, who hasn’t hoped for a REAL hoverboard? Once we know what gravity is “made of,” we can start making it easier to manipulate objects on earth and make space more habitable for human physiology. Either that or a puppy. Puppy sitting Divya Balu Pazhayannur – Director of Business Initiatives Christmas Wish 2021: I’m upgrading parts of my house over the holidays and browsing online for kitchen and laundry appliances. If you had told me that I would be spending three hours reading blogs on choosing the right cooktop for me, I would not have believed you. Does it have the right power, is it reliable, is it Wi-Fi enabled, can you talk to it – I’m kidding on that last one. Having said that, I’d love to get the Bosch Benchmark Gas Stovetop. Although I can’t speak to my appliance, its minimalist look has me writing it down on my wish list for Santa. I’ll even offer him some crispy dosas in exchange. Christmas Wish 2031: Apart from flying cars and personal robot assistants, I’d love to get the gift of better connectivity. I miss my family and friends in India, and it would be amazing to engage with them through holographic technology. I imagine it would allow for a much higher level of communication than today’s ‘talking head’ approach. Although do I want my family sitting with me in my living room? Still – I’d like to think a holograph would be just fantastic. Yury Ostrovsky – Sr. Technology Manager Christmas Wish 2021: I believe 2022 will be the year of VR toys. Virtual Reality is already popular, but I believe more applications will be developed in this area. We might see radio waves coming from different sources (Wi-Fi, LTE, 5G, BT, etc.) and visualize propagation in real-time. Christmas Wish 2031: “Prediction is very difficult, especially if it’s about the future” – Niels Bohr Kurt Semba – Principal Architect Christmas Wish 2021: The Crown from Neurosity. It helps you get and stay in a deep focus to improve your work and gaming results. Christmas Wish 2031: A non-evasive health device that can quickly look deep into your body and cells and explain why you are not feeling well today. Jon Filson – Senior Producer, Content Christmas Wish 2021: I want a large rollable TV by LG. In part because I watch a lot of football. And while I have a Smart TV, I still can’t get it to connect to my Bluetooth speaker … so while I love it, I want it to work better, and isn’t that so often the way with tech? But more than that, I don’t like and have never liked that rooms have to be designed around TVs. They are big, which is fine, but they are often in the way, which is less so. They should disappear when not in use. It’s $100,000 so I don’t expect it any time soon. But it’s an idea whose time has come. Christmas Wish 2031: I cheated on this one and asked my 12-year-old son Jack what he would want. It’s the portal gun, from Rick and Morty, a show in which a crazed scientist named Rick takes his grandson Morty on wacky adventures in a multi-verse. That last part is important to me. Kids today are already well into multi-verses, while we adults are just struggling to make one decent Metaverse. The next generation is already way ahead of us digitally speaking, it’s clear. Alexey Reznik – Senior UX Designer Christmas Wish 2021: This awesome toy: DJI Mavic 2 Pro – Drone Quadcopter UAV with Hasselblad Camera 3-Axis Gimbal HDR 4K Video Adjustable Aperture 20MP 1″ CMOS Sensor, up to 48mph, Gray Christmas Wish 2031: Something along these lines: BMW Motorrad VISION NEXT 100 BMW Motorcycle Michael Rash – Distinguished Engineer – Security Christmas Wish 2021: Satechi USB-C Multiport MX Adapter – Dual 4K HDMI. Christmas Wish 2031: A virtual reality headset that actually works. Alena Amir – Senior Content and Communications Manager Christmas Wish 2021: With conversations around VR/AR and the metaverse taking the world by storm, Santa could help out with an Oculus Quest. Purely for research purposes of course! Christmas Wish 2031: The 1985 movie, Back to the Future, was a family favorite and sure we didn’t get it all exactly right by 2015 but hey, it’s almost 2022! About time we get those hoverboards! David Coleman – Director of Wireless Christmas Wish 2021: Well, it looks like drones are the #1 wish item for 2021, and I am no exception. My wife and I just bought a home in the mountains of Blue Ridge, Georgia, where there is an abundance of wildlife. I want a state-of-the-art drone for bear surveillance. Christmas Wish 2031: In ten years, I will be 71 years old, and I hope to be at least semi-retired and savoring the fruits of my long tech career. Even though we are looking to the future, I want a time machine to revisit the past. I would travel back to July 16th, 1969, and watch Apollo 11 liftoff from Cape Kennedy to the moon. I actually did that as a nine-year-old kid. Oh, and I would also travel back to 1966 and play with my Rock’Em – Sock’Em Robots. Rock'em Sock'em Robots To summarize, our peeps in the Office of the CTO all envision Christmas 2031, where the way we interact as a society will have progressed. In 2021, we already have unlimited access to information, so future tech toys might depend less on magical new technologies and more on the kinds of experiences these new technologies can create. And when those experiences can be shared across the globe in real-time, the world gains an opportunity to learn from each other and grow together in ways that would never have been possible.

Data Science from Scratch Implemented in Swift

This repository contains codes starting from the basic machine learning to advanced topics in Ipython Notebooks.

Data Science Master with Gen AI Crash Course from Scratch

A collection of notebooks based on "Data Science From Scratch" 2nd Edition (O'Reilly, Joel Grus)

This repository contains my implementation of the algorithms described in the book "Data Science From Scratch" by Joel Grus. Please scroll down for description of each file.

Notes on "Data Science from Scratch" by Joel Grus

I am sharing lessons in various Python Libraries from scratch to intermediate including practice sets which were useful into my journey of Data Science.

No description available

based on https://github.com/joelgrus/data-science-from-scratch

A built from scratch OS strictly for training data science models.