Predict stock prices using LSTM networks in PyTorch. This project covers data preprocessing, sliding window creation, model training with early stopping, and evaluation with RMSE/MAE/MAPE. Includes visualizations of training loss, predicted vs actual prices, and short-horizon forecasts.
What is the AmirhosseinHonardoust/Stock-LSTM-Forecasting GitHub project? Description: "Predict stock prices using LSTM networks in PyTorch. This project covers data preprocessing, sliding window creation, model training with early stopping, and evaluation with RMSE/MAE/MAPE. Includes visualizations of training loss, predicted vs actual prices, and short-horizon forecasts.". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.
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