{"id":24520442,"url":"https://github.com/adudhe01/stocktrendpredictor","last_synced_at":"2026-04-10T16:39:27.016Z","repository":{"id":272573961,"uuid":"917049643","full_name":"ADudhe01/StockTrendPredictor","owner":"ADudhe01","description":"Stock Trend Prediction is a machine learning app that predicts stock prices using historical data. 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It uses historical stock data to train the model and makes predictions on future prices. The app is built with Streamlit for an interactive user interface where users can input stock tickers and visualize price trends, moving averages, and predictions.\n\n## Installation\n\nTo run this project locally, follow the steps below:\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/yourusername/StockTrendPredictor.git\n   cd StockTrendPredictor\n   ```\n2. Create a virtual environment (optional but recommended):\n  ```bash\n  python3 -m venv myenv\n  source myenv/bin/activate \n  ```\n  On Windows,\n  ```bash\n  use myenv\\Scripts\\activate\n  ```\n\n3. Install the required libraries:\n  ```bash\n  pip install -r requirements.txt\n  ```\n4. Make sure you have the keras_model.h5 model file in your project directory. This is the pre-trained model that the application uses to predict stock trends.\n\n## Usage:\nTo run the application, use the following command:\n  ```bash\n  streamlit run app.py\n```\nEnter a stock ticker (e.g., AAPL for Apple Inc.) when prompted. The app will download historical stock data and show the following visualizations:\n - Stock Data: Descriptive statistics of the stock from 2000 to the present.\n - Price vs Time: A plot of the closing price over time.\n - Moving Averages: A chart showing the closing price along with 100-day and 200-day moving averages.\n - Predictions vs Original: A comparison of the model's predictions against the actual stock prices.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadudhe01%2Fstocktrendpredictor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadudhe01%2Fstocktrendpredictor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadudhe01%2Fstocktrendpredictor/lists"}