Welcome to the Personalized Stock Investment Advisor! This machine learning-powered recommendation system provides users with personalized stock recommendations based on historical performance, market trends, and user preferences.
The Personalized Stock Investment Advisor is a recommendation system that assists users in making informed stock market decisions. Using a combination of collaborative and content-based filtering, the advisor recommends stocks for users to buy, hold, or sell based on their unique profiles and market data. This project leverages machine learning and data analytics to optimize investment decisions for individual users.
Collaborative Filtering: Recommends stocks based on preferences and behaviors of similar users.
Content-Based Filtering: Recommends stocks by analyzing stock attributes (e.g., market cap, P/E ratio, sector).
User Profiles: Customizable profiles to tailor recommendations to different risk levels and investment goals.
Market Data Analysis: Integrates historical data, technical indicators, and market sentiment.
Personalized Dashboard: View stock recommendations, analysis, and track your portfolio.
Collaborative Filtering: Uses user-based and item-based filtering to provide stock recommendations based on user similarity.
Content-Based Filtering: Analyzes stock attributes, including sector, market cap, P/E ratio, and past performance metrics to match stocks with user preferences.
Hybrid Model: Combines collaborative and content-based methods for improved recommendation accuracy and diversity.
Sentiment Analysis: Analyzes stock-related news to adjust recommendations based on current sentiment.
Example of Model Workflow:
User Profile Generation: Collects and processes data on user behavior, preferences, and portfolio composition.
Similarity Computation: Calculates similarities between users and stocks.
Recommendation Engine: Generates stock recommendations based on both collaborative and content-based filtering results.
We welcome contributions! Please follow these steps:
Fork this repository.
Create a new branch (git checkout -b feature/YourFeature).
Commit your changes (git commit -m 'Add new feature').
Push to the branch (git push origin feature/YourFeature).
Open a pull request.
Please ensure all new code is tested and follows best practices.
Enjoy making smarter investment decisions with the Personalized Stock Investment Advisor!