{"id":22962509,"url":"https://github.com/cs2219/recommender_system","last_synced_at":"2026-05-05T12:32:51.846Z","repository":{"id":263013738,"uuid":"889063510","full_name":"CS2219/Recommender_system","owner":"CS2219","description":"Recommendation system for Stock market","archived":false,"fork":false,"pushed_at":"2024-11-28T08:14:17.000Z","size":6203,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-07T18:18:15.207Z","etag":null,"topics":["datapipeline","machine-learning","newsapi","postgresql","project-management","random-forest-classifier","streamlit","tweepy-api","yfinance-api"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CS2219.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-15T14:39:43.000Z","updated_at":"2024-11-28T08:14:21.000Z","dependencies_parsed_at":null,"dependency_job_id":"5b289c62-cff3-4bbf-8a2e-6b02d917c8ab","html_url":"https://github.com/CS2219/Recommender_system","commit_stats":null,"previous_names":["cs2219/recommender_system"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CS2219%2FRecommender_system","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CS2219%2FRecommender_system/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CS2219%2FRecommender_system/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CS2219%2FRecommender_system/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CS2219","download_url":"https://codeload.github.com/CS2219/Recommender_system/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246749228,"owners_count":20827470,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["datapipeline","machine-learning","newsapi","postgresql","project-management","random-forest-classifier","streamlit","tweepy-api","yfinance-api"],"created_at":"2024-12-14T19:17:11.744Z","updated_at":"2026-05-05T12:32:46.822Z","avatar_url":"https://github.com/CS2219.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Buy/Sell recommendation system\nThis project is an AI-powered Stock Recommendation System designed to provide actionable insights such as \"Buy\" or \"Sell\" recommendations for stocks. By integrating data from multiple sources, applying advanced machine learning techniques, and presenting a user-friendly interface, this system empowers users to make data-driven investment decisions.\n\n\n**Features**\n###### Smart Data Integration:\n\nYahoo Finance API: Provides historical stock data.\nNews API: Delivers news articles for sentiment analysis.\nTwitter API: Captures real-time social sentiment about stocks.\nAlpha Vantage API: Supplies additional technical indicators for deeper analysis.\nMachine Learning for Predictions:\n\nPredicts stock movements using a Random Forest Classifier trained on historical data and technical indicators.\nCombines financial indicators (e.g., RSI, moving averages) with sentiment analysis for a holistic view.\nInteractive UI with Streamlit:\n\nUser-friendly interface to explore stock trends, visualize technical indicators, and get \"Buy\" or \"Sell\" recommendations.\nOffers interactive charts and insights to help users quickly analyze stock performance.\n###### Data Storage:\n\nUses PostgreSQL to store fetched data, ensuring fast and scalable access to historical and real-time datasets.\n**How It Works**\n###### Data Gathering:\nThe system fetches stock prices, technical indicators, and sentiment data from news articles and tweets.\n\n###### Data Processing \u0026 Feature Engineering:\n\nCalculates essential indicators like moving averages, Bollinger Bands, and RSI.\nPerforms sentiment analysis to assess market mood.\n###### Model Training:\n\nTrains a Random Forest Classifier on historical stock data combined with sentiment metrics.\nOptimized for accurate predictions of stock trends, with cross-validated accuracy of over 85%.\n###### Recommendation \u0026 Visualization:\n\nProvides \"Buy\" or \"Sell\" predictions for selected stocks.\nVisualizes key data points like stock prices, moving averages, and sentiment trends in real time.\n**Example Use Case**\n\nA user can:\n\nEnter a stock ticker (e.g., AAPL or TSLA).\nView the system's recommendation: \"Buy\" or \"Sell\".\nExplore visualized trends such as moving averages, RSI, and historical price data.\nGain confidence in decision-making by checking sentiment analysis from news and Twitter.\n###### Why You'll Love This\nThis system is perfect for anyone who:\n\nWants data-driven insights for their stock trades.\nValues an easy-to-use interface to understand complex stock trends.\nAims to combine technical analysis with market sentiment for smarter investment decisions.\nWhether you're a seasoned trader or a curious investor, this recommendation system will elevate your stock analysis game!","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcs2219%2Frecommender_system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcs2219%2Frecommender_system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcs2219%2Frecommender_system/lists"}