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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

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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](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 🌳
* ExtraTreesRegressor 🌲
* LinearRegression βž–
* KNeighborsRegressor 🀝
* LSTM implementation πŸ”„

## 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](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.