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https://github.com/samadpls/stockseer-api
Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.
https://github.com/samadpls/stockseer-api
extratreesregressor fastapi kneighborsclassifier linear-regression lstm machine-learning-algorithms open-source random-forest stock-price-prediction
Last synced: 3 days ago
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Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.
- Host: GitHub
- URL: https://github.com/samadpls/stockseer-api
- Owner: samadpls
- License: mit
- Created: 2024-05-14T18:45:10.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-11-02T14:33:27.000Z (3 months ago)
- Last Synced: 2024-11-02T15:25:23.788Z (3 months ago)
- Topics: extratreesregressor, fastapi, kneighborsclassifier, linear-regression, lstm, machine-learning-algorithms, open-source, random-forest, stock-price-prediction
- Language: Python
- Homepage:
- Size: 235 KB
- Stars: 5
- Watchers: 2
- Forks: 2
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## StockSeer-API `(Stock Price Prediction API)`
![Supported python versions](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10%20%7C%203.11-blue)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License](https://img.shields.io/badge/License-MIT%202.0-blue.svg)](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 π³
* ExtraTreesRegressor π²
* LinearRegression β
* KNeighborsRegressor π€
* LSTM implementation π## Data Source:
This application utilizes the Yahoo Finance API to retrieve historical stock data for training and prediction purposes.
## Featuresβ¨
* 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: Predictingoogle
Stock Price**| Input | Response|
raph |
|------|---------|---------|
|![image](https://github.com/samadpls/stockseer-api/assets/94792103/b6860128-41fb-463d-908d-433b11f3d826)|![image](https://github.com/samadpls/stockseer-api/assets/94792103/5ef2c728-22e3-4e9c-9049-b8b8ceddc276)||
## Installation
1. Ensure you have Python installed.
2. Create a new virtual environment (recommended).
3. Activate the virtual environment.
4. Install required dependencies:```bash
pip install -r requirements.txt
```## Usage
1. Run the application:
```bash
uvicorn app:app --reload
```2. 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](https://github.com/Myrausman/StockSeer-Frontend).
## Disclaimer
**Important:** Stock price prediction is inherently uncertain. This application should not be used for making financial decisions.