- Developed a Stock Price Prediction project using machine learning algorithms to forecast stock prices for companies like AAPL, AMZN, GOOGL, IBM, MSFT, and NVDA.
- Implemented data fetching from Yahoo Finance using Python scripts for real-time stock data analysis.
- Built and trained machine learning models with scikit-learn for stock price prediction and evaluated performance using backtesting and k-fold cross-validation techniques.
- Designed interactive visualizations for algorithm comparison, backtesting results, and validation metrics using Matplotlib.
- Created a Streamlit application for real-time stock prediction visualization and user interaction.
- Utilized Jupyter Notebooks for exploratory data analysis and experimentation with different prediction models.
- Organized project structure with modular scripts and company-specific data folders for scalability and maintainability.
- Leveraged Python libraries such as
pandas,numpy,scikit-learn,matplotlib,streamlit, andyfinancefor data processing, modeling, and visualization.
Create a new conda environment:
conda create --name finance python=3.10Activate the new environment:
conda activate env_nameInstall the dependencies:
pip install -r requirements.txt