About this document
PyTorch for Sequential Data Handling by Samesh Bajracharya is a document available to read on EtoBox.
The document discusses handling sequential data using PyTorch, focusing on predicting electricity consumption based on historical data. It covers the importance of data splitting to avoid look-ahead bias, the creation of input sequences, and the implementation of various recurrent neural network architectures including RNNs, LSTMs, and GRUs. Additionally, it highlights the training and evaluation processes for these models, emphasizing the use of Mean Squared Error as the loss function for regression tasks.
- Author
- Samesh Bajracharya
- Language
- EN