https://github.com/surajkumar4-source/stock-price-predictor-app
Stock Price Predictor Web App, where the synergy of machine learning and real-time data delivers captivating insights into stock market trends. Explore its innovative features for dynamic and interactive predictions of stock prices
https://github.com/surajkumar4-source/stock-price-predictor-app
Last synced: 11 months ago
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Stock Price Predictor Web App, where the synergy of machine learning and real-time data delivers captivating insights into stock market trends. Explore its innovative features for dynamic and interactive predictions of stock prices
- Host: GitHub
- URL: https://github.com/surajkumar4-source/stock-price-predictor-app
- Owner: Surajkumar4-source
- Created: 2024-07-07T12:19:23.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-08T10:57:55.000Z (almost 2 years ago)
- Last Synced: 2025-06-01T19:18:35.132Z (12 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 2.84 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Stock Price Predictor Web App
## Project Overview
Welcome to the Stock Price Predictor Web App, where the synergy of machine learning and real-time data delivers captivating insights into stock market trends. Explore its innovative features for dynamic and interactive predictions of stock prices.
Here's a closer look at what the app offers:
## Key Features
- **User-Friendly Interface**: Built with Streamlit, the app offers a seamless and interactive user experience, allowing users to input their desired stock symbols and view predictions.
- **Historical Data Analysis**: Fetches historical stock data from Yahoo Finance, enabling users to visualize past performance.
- **Real-Time Predictions**: Utilizes a pre-trained LSTM (Long Short-Term Memory) model to predict future stock prices.
- **Visual Insights**: Provides detailed plots comparing original and predicted stock prices, along with future price projections.
## How It Works
1. **Input Stock Symbol**: Users can enter any stock symbol (default is Bitcoin - BTC-USD).
2. **Data Fetching**: The app retrieves historical stock data from Yahoo Finance, dating back ten years.
3. **Model Prediction**: Using the LSTM model, the app predicts future stock prices based on historical data.
4. **Visualization**: The app generates various plots to visualize historical, predicted, and future stock prices.
## Technical Details
- **Streamlit**: An open-source app framework for creating and sharing custom web apps for machine learning and data science.
- **Keras**: A powerful deep learning library used for training the LSTM model.
- **Yahoo Finance API**: Provides reliable and up-to-date stock market data.
- **Matplotlib**: A plotting library used to create static, interactive, and animated visualizations.
## Visualizations
- **Historical Data**: Displays the historical closing prices of the selected stock.
- **Predicted vs. Actual Prices**: Compares the model's predictions with actual stock prices to assess accuracy.
- **Future Price Predictions**: Projects future stock prices based on the model's predictions.
## Future Enhancements
- **Model Improvements**: Continuously refine the model for better accuracy and performance.
- **User Feedback Integration**: Incorporate user feedback to improve the app's functionality and usability.
## How to Use
1. **Clone the repository**:
```bash
git clone https://github.com/Surajkumar4-source/stock-price-predictor-app.git
cd stock-price-predictor-app
2. **Install the necessary libraries**:
```bash
pip install streamlit keras yfinance pandas streamlit numPy matplotlib datetime sklearn(Scikit-learn):
3.**Run the app**:
## DEMO
https://github.com/Surajkumar4-source/Stock-Price-Predictor-App/assets/122175764/34bf14dd-83af-48a8-b2a5-afe5961ea7bf