https://github.com/jxgamessi/stock-price-prediction-using-lstm-and-rnn
This project builds an interactive Streamlit app for stock price forecasting. It uses an ensemble of Stacked LSTM and Simple RNN models trained on user-uploaded Excel datasets. The app visualizes Bollinger Bands, model performance, and predicts the next day's stock price, offering clear insights with real-time charts and accuracy metrics.
https://github.com/jxgamessi/stock-price-prediction-using-lstm-and-rnn
ensamble-methods machine-learning nueral-networks stock-price-prediction streamlit-dashboard timeseries-forecasting
Last synced: 3 months ago
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This project builds an interactive Streamlit app for stock price forecasting. It uses an ensemble of Stacked LSTM and Simple RNN models trained on user-uploaded Excel datasets. The app visualizes Bollinger Bands, model performance, and predicts the next day's stock price, offering clear insights with real-time charts and accuracy metrics.
- Host: GitHub
- URL: https://github.com/jxgamessi/stock-price-prediction-using-lstm-and-rnn
- Owner: Jxgamessi
- Created: 2023-10-19T10:53:33.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-04-29T06:50:23.000Z (5 months ago)
- Last Synced: 2025-06-09T03:34:56.828Z (4 months ago)
- Topics: ensamble-methods, machine-learning, nueral-networks, stock-price-prediction, streamlit-dashboard, timeseries-forecasting
- Language: Python
- Homepage:
- Size: 848 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files: