Stock Price Prediction using Machine Learning Techniques

This project focuses on predicting stock prices using advanced machine learning models. By analyzing historical market data, we aim to forecast future price movements and provide insights that can guide trading decisions.

Features

• Predicts future stock prices based on historical data.
• Utilizes models such as LSTM, ARIMA, and Linear Regression for time series forecasting.
• Visualizes predicted vs. actual prices for performance comparison.
• Provides trading signals based on prediction results.

Installation

To set up the stock price prediction system on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/username/stock-price-prediction.git
   cd stock-price-prediction

2. Set Up Virtual Environment (Optional but Recommended)

   python3 -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Required Packages

   pip install -r requirements.txt

Usage

To start predicting stock prices, run the main script with your desired stock data:

python stock_price_prediction.py --input