Stock Price Predictor App

This repository contains a web-based Stock Price Predictor application that uses historical stock data and a machine learning model to predict future stock prices. The app is built using Streamlit and TensorFlow, leveraging financial data from Yahoo Finance.

Features

• Real-Time Stock Data: Fetches the latest 20 years of stock data using Yahoo Finance.
• Moving Averages: Displays the moving averages (MA) for 100, 200, and 250 days.
• Predictive Modeling: Predicts future stock prices based on historical data using a pre-trained machine learning model.
• Data Visualization: Visualizes the actual vs. predicted stock prices.

Requirements

• Python 3.8 or later
• Streamlit
• TensorFlow (Keras)
• Pandas
• Numpy
• Matplotlib
• scikit-learn
• yfinance

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/stock-price-predictor.git
   cd stock-price-predictor

Step 3: Install Required Python Packages

pip install -r requirements.txt

Step 4: Download the Pre-Trained Model

You need to download the pre-trained model and place it in the root directory. The model file should be named Latest_stock_price_model.keras.

# Example command to download the model (replace with actual command or link)
# wget -O Latest_stock_price_model.keras <model_download_link>

Step 5: Run the Streamlit App

streamlit run web_stock_price_predictor.py