What are Dataset and DataLoader in PyTorch?

The Dataset class in PyTorch provides an interface for accessing data. It allows you to define how your data should be read, transformed, and accessed. The DataLoader class, on the other hand, provides an efficient way to iterate over your dataset in batches, which is crucial for training models.

PyTorch is a powerful deep-learning library that offers flexible and efficient tools for handling data. Among its many features, the Dataset and DataLoader classes stand out for their ability to streamline data preprocessing and loading. This article will guide you through the process of using these classes for custom data, from defining your dataset to iterating through batches of data during training.