Loading and normalizing datasets

Check your knowledge

What is the difference between a PyTorch DataSet and a PyTorch DataLoader

A DataSet is designed to work with batches of data while a DataLoader is designed for retrieval of individual data items.

A DataSet is designed for retrieval of individual data items while a DataLoader is designed to work with batches of data.

The DataLoader class is the parent of the DataSet class

The DataSet class is the parent of the DataLoader class

Transforms in PyTorch are designed to:

Perform some manipulation of the data to make it suitable for training.

Convert input tensors into an output tensor that contains a prediction.

Convert data items into visual representations.

You must answer all questions before checking your work.