Time Series Forecasting with PyTorch: Predicting Stock Prices
In this project, we aim to predict stock prices using a Long Short-Term Memory (LSTM) neural network, a powerful model for time series forecasting.
The LSTM model is trained and evaluated on historical stock price data to make predictions on future stock prices. The code walkthrough provides an explanation of each code segment, highlighting the key functionalities and transformations performed at different stages of the process. The project utilizes popular Python libraries such as PyTorch, NumPy, pandas, and matplotlib to handle the data, build the model, and visualize the results.
Download the source code from the link in comment section.