StockBot powered by Groq: Lightning Fast AI Chatbot that Responds With Live Interactive Stock Charts, Financials, News, Screeners, and More. Powered by Llama3-70b on Groq, Vercel AI SDK, and TradingView Widgets.

A dynamic financial literacy app with Arthsathi AI chatbot, finance blogs, market trends, SIP calculator, and a quiz for effortless finance learning.

This repository contains implementations of Retrieval-Augmented Generation (RAG) in Jupyter notebooks. It includes examples of building chatbots with and without history, processing PDFs with RAG, and using DeepSeek models for local RAG and financial document analysis.

An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68] Decision trees Main article: Decision tree learning Decision tree learning uses a decision tree as a predictive model to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). It is one of the predictive modeling approaches used in statistics, data mining, and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically real numbers) are called regression trees. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data, but the resulting classification tree can be an input for decision making. Support vector machines Main article: Support vector machines Support vector machines (SVMs), also known as support vector networks, are a set of related supervised learning methods used for classification and regression. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other.[69] An SVM training algorithm is a non-probabilistic, binary, linear classifier, although methods such as Platt scaling exist to use SVM in a probabilistic classification setting. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the kernel trick, implicitly mapping their inputs into high-dimensional feature spaces. Illustration of linear regression on a data set. Regression analysis Main article: Regression analysis Regression analysis encompasses a large variety of statistical methods to estimate the relationship between input variables and their associated features. Its most common form is linear regression, where a single line is drawn to best fit the given data according to a mathematical criterion such as ordinary least squares. The latter is often extended by regularization (mathematics) methods to mitigate overfitting and bias, as in ridge regression. When dealing with non-linear problems, go-to models include polynomial regression (for example, used for trendline fitting in Microsoft Excel[70]), logistic regression (often used in statistical classification) or even kernel regression, which introduces non-linearity by taking advantage of the kernel trick to implicitly map input variables to higher-dimensional space. Bayesian networks Main article: Bayesian network A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet. A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform inference and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Genetic algorithms Main article: Genetic algorithm A genetic algorithm (GA) is a search algorithm and heuristic technique that mimics the process of natural selection, using methods such as mutation and crossover to generate new genotypes in the hope of finding good solutions to a given problem. In machine learning, genetic algorithms were used in the 1980s and 1990s.[71][72] Conversely, machine learning techniques have been used to improve the performance of genetic and evolutionary algorithms.[73] Training models Usually, machine learning models require a lot of data in order for them to perform well. Usually, when training a machine learning model, one needs to collect a large, representative sample of data from a training set. Data from the training set can be as varied as a corpus of text, a collection of images, and data collected from individual users of a service. Overfitting is something to watch out for when training a machine learning model. Federated learning Main article: Federated learning Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices. For example, Gboard uses federated machine learning to train search query prediction models on users' mobile phones without having to send individual searches back to Google.[74] Applications There are many applications for machine learning, including: Agriculture Anatomy Adaptive websites Affective computing Banking Bioinformatics Brain–machine interfaces Cheminformatics Citizen science Computer networks Computer vision Credit-card fraud detection Data quality DNA sequence classification Economics Financial market analysis[75] General game playing Handwriting recognition Information retrieval Insurance Internet fraud detection Linguistics Machine learning control Machine perception Machine translation Marketing Medical diagnosis Natural language processing Natural language understanding Online advertising Optimization Recommender systems Robot locomotion Search engines Sentiment analysis Sequence mining Software engineering Speech recognition Structural health monitoring Syntactic pattern recognition Telecommunication Theorem proving Time series forecasting User behavior analytics In 2006, the media-services provider Netflix held the first "Netflix Prize" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model to win the Grand Prize in 2009 for $1 million.[76] Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[77] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[78] In 2012, co-founder of Sun Microsystems, Vinod Khosla, predicted that 80% of medical doctors' jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[79] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognized influences among artists.[80] In 2019 Springer Nature published the first research book created using machine learning.[81] Limitations Although machine learning has been transformative in some fields, machine-learning programs often fail to deliver expected results.[82][83][84] Reasons for this are numerous: lack of (suitable) data, lack of access to the data, data bias, privacy problems, badly chosen tasks and algorithms, wrong tools and people, lack of resources, and evaluation problems.[85] In 2018, a self-driving car from Uber failed to detect a pedestrian, who was killed after a collision.[86] Attempts to use machine learning in healthcare with the IBM Watson system failed to deliver even after years of time and billions of dollars invested.[87][88] Bias Main article: Algorithmic bias Machine learning approaches in particular can suffer from different data biases. A machine learning system trained on current customers only may not be able to predict the needs of new customer groups that are not represented in the training data. When trained on man-made data, machine learning is likely to pick up the same constitutional and unconscious biases already present in society.[89] Language models learned from data have been shown to contain human-like biases.[90][91] Machine learning systems used for criminal risk assessment have been found to be biased against black people.[92][93] In 2015, Google photos would often tag black people as gorillas,[94] and in 2018 this still was not well resolved, but Google reportedly was still using the workaround to remove all gorillas from the training data, and thus was not able to recognize real gorillas at all.[95] Similar issues with recognizing non-white people have been found in many other systems.[96] In 2016, Microsoft tested a chatbot that learned from Twitter, and it quickly picked up racist and sexist language.[97] Because of such challenges, the effective use of machine learning may take longer to be adopted in other domains.[98] Concern for fairness in machine learning, that is, reducing bias in machine learning and propelling its use for human good is increasingly expressed by artificial intelligence scientists, including Fei-Fei Li, who reminds engineers that "There’s nothing artificial about AI...It’s inspired by people, it’s created by people, and—most importantly—it impacts people. It is a powerful tool we are only just beginning to understand, and that is a profound responsibility.”[99] Model assessments Classification of machine learning models can be validated by accuracy estimation techniques like the holdout method, which splits the data in a training and test set (conventionally 2/3 training set and 1/3 test set designation) and evaluates the performance of the training model on the test set. In comparison, the K-fold-cross-validation method randomly partitions the data into K subsets and then K experiments are performed each respectively considering 1 subset for evaluation and the remaining K-1 subsets for training the model. In addition to the holdout and cross-validation methods, bootstrap, which samples n instances with replacement from the dataset, can be used to assess model accuracy.[100] In addition to overall accuracy, investigators frequently report sensitivity and specificity meaning True Positive Rate (TPR) and True Negative Rate (TNR) respectively. Similarly, investigators sometimes report the false positive rate (FPR) as well as the false negative rate (FNR). However, these rates are ratios that fail to reveal their numerators and denominators. The total operating characteristic (TOC) is an effective method to express a model's diagnostic ability. TOC shows the numerators and denominators of the previously mentioned rates, thus TOC provides more information than the commonly used receiver operating characteristic (ROC) and ROC's associated area under the curve (AUC).[101] Ethics Machine learning poses a host of ethical questions. Systems which are trained on datasets collected with biases may exhibit these biases upon use (algorithmic bias), thus digitizing cultural prejudices.[102] For example, using job hiring data from a firm with racist hiring policies may lead to a machine learning system duplicating the bias by scoring job applicants against similarity to previous successful applicants.[103][104] Responsible collection of data and documentation of algorithmic rules used by a system thus is a critical part of machine learning. Because human languages contain biases, machines trained on language corpora will necessarily also learn these biases.[105][106] Other forms of ethical challenges, not related to personal biases, are more seen in health care. There are concerns among health care professionals that these systems might not be designed in the public's interest but as income-generating machines. This is especially true in the United States where there is a long-standing ethical dilemma of improving health care, but also increasing profits. For example, the algorithms could be designed to provide patients with unnecessary tests or medication in which the algorithm's proprietary owners hold stakes. There is huge potential for machine learning in health care to provide professionals a great tool to diagnose, medicate, and even plan recovery paths for patients, but this will not happen until the personal biases mentioned previously, and these "greed" biases are addressed.[107] Hardware Since the 2010s, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks (a particular narrow subdomain of machine learning) that contain many layers of non-linear hidden units.[108] By 2019, graphic processing units (GPUs), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[109] OpenAI estimated the hardware compute used in the largest deep learning projects from AlexNet (2012) to AlphaZero (2017), and found a 300,000-fold increase in the amount of compute required, with a doubling-time trendline of 3.4 months.[110][111] Software Software suites containing a variety of machine learning algorithms include the following: Free and open-source so

GPTStonks is a financial chatbot powered by LLMs and enhanced with data frameworks. It provides natural language conversation capabilities for financial topics, making it an ideal choice for a wide range of financial applications.

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An Intelligent Chatbot for Personalized Financial Services

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AI-powered financial assistant in Go with chatbot and receipt processing

Facebook Messenger Chatbot integrated with Live Agent and Financial Services Cloud

A financial chatbot powered by an LLM and retrieval-augmented generation.

Financial Stock Assistant Chatbot using ChatGPT

Developing a RAG-powered chatbot for CreditTrust Financial that analyzes customer complaints across five financial products. The AI tool retrieves relevant complaint narratives using semantic search and generates actionable insights, helping product managers identify trends faster. Built with Python, LangChain, FAISS/ChromaDB, and Gradio/Streamlit.

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Prospera is an AI-powered budgeting app that helps users manage their finances by analyzing spending patterns and providing personalized recommendations. It integrates real-time financial data and features a secure chatbot for quick financial insights.

Financial Literacy Gamification is a Minecraft-themed web app offering expert sessions, blogs, stock analysis games, and multi-player parties. It features a rewards system, real-time dashboard, and a chatbot for document support. Users engage in interactive learning, quizzes, and battles to boost financial skills.

Financial Advisor Chatbot assistant using LLM.

Chatbot for Stream / Financial Institutions Powered by Stream Chat and Dialogflow

InvestGPT is a financial chatbot utilizing GPT-4 and various APIs. It quickly delivers relevant financial information, answers questions, and provides real-time stock data, offering efficient financial assistance to users.

This Guidance demonstrates how organizations in the Financial Service Industry (FSI) can modernize their claims processing using digital technologies, such as automated chatbots, machine learning, and data analytics.

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Financial Q/A chatbot built using fine tuned Bert and RAG System

RAG Chatbot for Financial Analysis

Finbot is an AI-powered financial chatbot designed to analyse and provide insights on corporate financial performance from 10-K and 10-Q financial documents. This tool leverages langchain and RAG to make complex financial data easily accessible and understandable through a conversational interface.

Which of the following options best describes the role of Shared Hosting on a web server? Providing hosting for a single website owned by different people on multiple servers. Providing hosting for a single website owned by one person on one server. Providing hosting for multiple websites owned by different people on one server. Providing hosting for multiple websites owned by one person on one server. 3 Which of the following capabilities can a cPanel account user perform easily from within the cPanel account interface without the aid of a system administrator? File and configuration management. Relocating the physical server. Upgrading server hardware and equipment. Installing new database software. 1 File and configuration management. Which of the following options best describes a core benefit to using cPanel & WHM, as a web hosting provider operating on a cPanel & WHM environment? cPanel users are able to create new virtualization resources to help host their web applications. cPanel users are able to set up network tunnels to establish secure communication between servers. cPanel users are able to establish and self-manage their own network routing configurations. cPanel users are able to self-manage configurations and software, reducing the support demand on the web host. 4 cPanel users are able to self-manage configurations and software, reducing the support demand on the web host Which of the following options best describes one way that cPanel makes installation of cPanel & WHM an easy process? cPanel provides a single command that can be copied and pasted onto the command line. cPanel provides a single, 16-step procedure with comprehensive documentation to guide customers through each step. cPanel provides a single executable that can be launched using a remotely delivered API request. cPanel provides a single CD-ROM that can be mailed internationally, free of charge. 1 cPanel provides a single command that can be copied and pasted onto the command line. Which of the following statistics does a cPanel account have access to from within the cPanel account interface? Bandwidth usage Server CPU temperature Other accounts' disk usage Server startup logs 1 Bandwidth usage cPanel provides multiple database software options for server administrators to choose from. MySQL is one of these options. Which of the following indicates one of the other options that are supported and provided by cPanel? MariaDB MSSQL IBM DB2 MongoDB 1 MariaDB Assuming "domain.com" is replaced with your actual domain on a cPanel & WHM server, which of the following website addresses would not bring you to a cPanel login page? cpanel.domain.com domain.com www.domain.com/cpanel www.domain.com:2083 2 domain.com After logging into an email account's webmail interface, the account user can then perform which of the following tasks directly from within their email dashboard interface? Configure FTP settings. Configure spam filtering settings. Configure SSL certificates. Configure PHP version settings. 2 Configure spam filtering settings. Which of the following options indicates a cPanel & WHM feature that can provide users with access to the server's command line interface (or, CLI) directly from within the cPanel or WHM interfaces? Server Command Shell Server Control Terminal 4 Terminal Assuming that your server's IP address is '12.34.56.78', which of the following services could be reached by navigating to the following address in your browser? https://12.34.56.78:2087 Webhost Manager (WHM) cPanel Support Center (CPSC) Server Status Display (SSD) Systems Control Center (SCC) 4 Webhost Manager (WHM) What does the acronym WHM stand for, in cPanel & WHM? Wide Home Maker Web Hero Master Whole Host Manipulator Web Host Manager 4 Web Host Manager A user who has little-to-no experience in server management will be able to do what? Run various command line commands Use the product out-of-the-box Manage several Windows programs. Add RAM to the server 2 Use the product out-of-the-box Of the following options, which of these are cPanel & WHM features that would be of interest to a programmer or web developer? SSL AFK SMTP API API About how long does it take to set up a mailing-list in cPanel? 5m 1m 1h 10m 2 1m Which of the following choices describes the method that a customer would use to access their cPanel or WHM interfaces, once it's been installed on a server? Using a web browser, like Chrome or Firefox. Using a FTP application, like FileZilla or FireFTP. Using a search engine, like Google or Yahoo. Using a social media platform, like Facebook or LinkedIn. 1 Using a web browser, like Chrome or Firefox. Of the following features found in a cPanel account interface, which would most likely be considered as important to a beginner-level customer seeking a cPanel & WHM web host? Apache Handlers Perl Modules Email Forwarders SSH Access 1 Apache Handlers Of the following services, which of these can be managed by website owners using only their cPanel account interface? Firewall Configuration Database Server Upgrades Scheduled Tasks EasyApache 4 Configuration 3 Scheduled Tasks Which of the following features available in the cPanel account interface allows new website files to easily be created, uploaded and edited by the user, directly from within the cPanel interface? BoxTrapper File Handler File Manager MultiPHP Manager 3 File Manager Which of the following features found in the cPanel account interface will allow a cPanel account user to create subaccounts to give email, FTP, and webdisk access to additional users? File Manager Aliases User Manager Contact Information 3 User Manager Which of the following feature categories within a cPanel account interface will allow users to view their Bandwidth usage statistics? Email Metrics Advanced Domains 2 Metrics Which of the following online resources provided by cPanel is the ideal place for customers to submit cPanel & WHM feature ideas, improvements, and suggestions for our developers to consider? The cPanel Documentations Site cPanel University The cPanel Store The cPanel Feature Request Site 4 The cPanel Feature Request Site confirm Which of the following services does cPanel provide for every customer with an active cPanel license? Free technical support, support services, and customer assistance. Free technical support with our automated AI chatbot, cPanel Pete. No human support is available. Free server-build assessments and cost estimates. Free quotes on the cost of getting technical support from cPanel. 1 Free technical support, support services, and customer assistance. confirm from website Which of the following options indicates the office hours in which the cPanel Technical Support Analyst team is available? 24 hours a day, 365 days a year. 7 days a week, from 9AM to 5PM, Central Standard Time. Weekdays from 6AM to 6PM, Central Standard Time. 12 hours a day, 182.5 days a year. 1 24 hours a day, 365 days a year. Which of the following types of applications can be created and managed with the cPanel account interface's Application Manager feature? 'Amethyst on Tracks' Applications Node.js Applications YAML Applications PHP Applications 2 Node.js Applications confirm Which of the following services does our support team provide for customers coming from DirectAdmin, Plesk, and Ensim control panels? Free estimates. Free migration. Free optimization. Free coupons. 2 Free migration confirm from website We offer free migration services for customers who use the following ... Plesk®. DirectAdmin. Ensim®. Which of the following options indicates the frequency of major updates being released for the product each year? Bi-annual releases. every two years Quarterly releases. every 3 months Weekly releases. Centennial releases. hundread year 2 Quarterly releases confirm from website Which of the following indicates cPanel's flagship product? CoreProc & Litespeed AppConfig & cPsrvd EasyApache & cPHulk cPanel & WHM 3 EasyApache & cPHulk In 2017, cPanel celebrated its anniversary of how many years? 5 years 50 years 20 years 100 years 20 confirm Which of the following categories found within the WHM interface provide a number of helpful features for administrators to secure their server with? Policy Control Severity Monitor Security Center Server Command 3 Security Center Which of the following options indicates an actual interface within WHM that will allow administrators to specify which features are available to specific users or packages on the server? Adjust Package Option Selector Feature Manager Policy Manager 3 Feature Manager confirm from whm Which of the following options best describes WHM's EasyApache feature? An administrative feature that makes web server software changes fast and easy. An administrative feature that makes processor overclocking calculation estimates fast and easy. An administrative feature that makes printer calibration fast and easy. An administrative feature that makes email queue management fast and easy. 1 An administrative feature that makes web server software changes fast and easy. cPanel Support will provide which of the following services for customers that request it? Performing cPanel & WHM installations. Performing TSLC MicroPort adjustments. Providing financial advice. Providing IANA-approved routing. 1 Performing cPanel & WHM installations. Which of the following options best describes an interface within WHM that allows administrators to easily create sets of limitations for different types of accounts, commonly based on some arrangement of web host pricing options? Packages >> Add a Package Limitations >> Create Limits Types >> New Type Features >> Set Restrictions 1 Which of the following options indicates an actual feature included with EasyApache 4 that allows accounts on the same server to use different versions of PHP simultaneously? cPPHP MyPHP YourPHP MultiPHP 4 MultiPHP Which of the following options are important for a customer to have on their server, in order to allow their cPanel & WHM installation to be licensed properly? A Google Mail address. A home postal address. A public IP address. A domain name address. 3 A public IP address. Which of the following options indicates an actual feature within WHM that can be used to migrate one or more accounts between servers? Transfer Tool Account Relocate Server Profiler Migration Assist 1 Which of the following options best describes a benefit of using SSL certificates to secure websites hosted on your server? They ensure that communication between your server and the internet is safe and encrypted. They ensure that communication between your server and the internet is officially approved by the OIBC (Official Internet Bureau of Communications). They ensure that communication between your server and the internet is only visible by explicitly allowed individuals. They ensure that communication between your server and the internet cannot occur. 1 They ensure that communication between your server and the internet is safe and encrypted. Which of the following Content Management Systems (CMS) have a feature built into cPanel that allows customers to manage its installations and updates from within the cPanel account interface? Joomla! Drupal WordPress Typo3 3 WordPress Which of the following options indicates an actual security feature of cPanel & WHM servers that acts as a safety net for website security by using rules created by security authorities to intercept malicious attempts at exploiting websites and web applications? AuthMod LockDown ModSecurity SecurityNet 3 ModSecurity Which of the following operating systems can cPanel & WHM NOT be installed or used on? Amazon Linux Servers Windows Servers CentOS Servers Redhat Servers 2 Windows Servers Which of the following features available in WHM can help customers migrate easily between servers? Feature Manager Transfer Tool EasyApache 4 Security Advisor Transfer Tool Which of the following options best describes the role of a web hosting control panel? Software on the operating system that provides a visual read-out of server specifications and statistics, such as temperature and fan speed. Software on the operating system that provides a basic suite of office utilities, such as a word processor, spreadsheet manager, and a presentation designer. Software on the operating system that provides a graphical interface designed to help automate server administration tasks. Software on the operating system that provides a desktop environment similar to Microsoft Windows or Apple's MacOS. Software on the operating system that provides a graphical interface designed to help automate server administration tasks. Which of the following operating systems are supported by cPanel & WHM's official system requirements? Windows Server 2018 CentOS Server Debian Server Ubuntu Server CentOS Server

Streamlit chatbot for financial document analysis

This repository hosts the codebase for a Financial Advisor landing page integrated with a chatbot designed to answer frequently asked financial questions. The project demonstrates the integration of front-end web development with the Python Flask framework and a chatbot powered by ML and NLP.

A finance tracking app that provides detailed insights about your expenses using AI, allowing you to chat and call interaction with your financial data.

This Ai Financial Assistant Chatbot is an AI-powered tool for real-time stock market insights. It uses OpenAI, Pandas, YFinance, Matplotlib, and Streamlit to provide fast and accurate financial data, making it a valuable resource for investors and finance enthusiasts.

StockBot powered by Groq: Lightning Fast AI Chatbot that Responds With Live Interactive Stock Charts, Financials, News, Screeners, and More. Powered by Llama3-70b on Groq, Vercel AI SDK, and TradingView Widgets.