STOCK-PRICE-PREDICTION-USING-LSTM-AND-RNN
PublicThis 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.
ensamble-methodsmachine-learningnueral-networksstock-price-predictionstreamlit-dashboardtimeseries-forecasting
Creat：2023-10-19T18:53:33
Update：2025-04-29T14:50:26
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