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Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.

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StockSeer-API (Stock Price Prediction API)

Supported python versions Code style: black License

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 🔄

Data Source:

This application utilizes the Yahoo Finance API to retrieve historical stock data for training and prediction purposes.

Features✨

  • Download and preprocess historical stock data
  • Train a stock price prediction model of your choice
  • Make predictions on future closing stock prices

Working Prototype

Example: Predicting oogle Stock Price

Input Response raph
image image

Installation

  1. Ensure you have Python installed.
  2. Create a new virtual environment (recommended).
  3. Activate the virtual environment.
  4. Install required dependencies:
pip install -r requirements.txt

Usage

  1. Run the application:
uvicorn app:app --reload
  1. 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.

Credits

  • Maira Usman: Developed the GUI for this project. You can find the code here: Link to StockSeer-Frontend.

Disclaimer

Important: Stock price prediction is inherently uncertain. This application should not be used for making financial decisions.