This project is a FastAPI application that predicts the closing stock price for a given company based on user-specified parameters. It utilizes various machine learning models for prediction, including:
- RandomForestRegressor 🌳
- ExtraTreesRegressor 🌲
- LinearRegression ➖
- KNeighborsRegressor 🤝
- LSTM implementation 🔄
This application utilizes the Yahoo Finance API to retrieve historical stock data for training and prediction purposes.
- Download and preprocess historical stock data
- Train a stock price prediction model of your choice
- Make predictions on future closing stock prices
Example: Predicting oogle Stock Price
Input | Response | raph |
---|---|---|
- Ensure you have Python installed.
- Create a new virtual environment (recommended).
- Activate the virtual environment.
- Install required dependencies:
pip install -r requirements.txt
- Run the application:
uvicorn app:app --reload
- Access the API documentation in your web browser: http://127.0.0.1:8000/docs
The documentation provides instructions on interacting with the API to make predictions.
- Maira Usman: Developed the GUI for this project. You can find the code here: Link to StockSeer-Frontend.
Important: Stock price prediction is inherently uncertain. This application should not be used for making financial decisions.