📈 Stock Market Trend Prediction App

An AI-powered web application built with Streamlit that predicts future stock prices using a Long Short-Term Memory (LSTM) deep learning model trained on historical market data.

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🚀 Demo

🔗 Live App on Streamlit

🚀 Video Demo

Stock-Prediction.webm

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📌 Features

• Predicts future stock closing prices using an LSTM model.
• User-friendly Streamlit interface.
• Upload a CSV file with historical stock data.
• Generates predictions for 1–30 days ahead.
• Provides interactive charts for historical + predicted prices.
• Includes an About Me sidebar with portfolio links.

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🔍 Usage

1. Open the app in your browser.
2. Upload a CSV file containing historical stock data.
   • Must contain a column: Close (or Adj Close).
3. Choose the number of days you want predictions for.
4. Click Predict.
5. Get results:
   • 📊 Table of predicted prices.
   • 📈 Graph combining historical + predicted trends.

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📊 Dataset

The app works with stock market historical data.

• You can fetch stock data using Yahoo Finance API (yfinance) or download from any trusted source.
• Columns required:
  • Date
  • Open
  • High
  • Low
  • Close or Adj Close
  • Volume

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⚙️ Tech Stack

• Python 3.9+
• Streamlit (Frontend Web App)
• NumPy & Pandas (Data Processing)
• Matplotlib & Plotly (Visualizations)
• Scikit-learn (Preprocessing & Scaling)
• TensorFlow / Keras (LSTM Deep Learning Model)

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📸 Screenshots

🏠 Home Page

📊 Prediction Results

📊 Prediction Results

📊 Prediction Results

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👨‍💻 Author

Mirza Yasir Abdullah Baig

• 🌐 Kaggle
• 💼 LinkedIn
• 💻 GitHub

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❤️ Acknowledgements

• Yahoo Finance API (yfinance)
• Streamlit Documentation
• Scikit-learn
• TensorFlow/Keras

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⚠️ Disclaimer

This project is for educational and research purposes only and should NOT be considered as financial advice. Always do your own research before investing in the stock market.

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