Working with Data in PyTorch

In this tutorial, we'll deal with a fundamental challenge in Machine Learning and Deep Learning that is easier said than done: loading and handling different types of data. Specifically, we'll cover:

• Looking at built-in datasets in-depth
• Using the Dataloader class
• Using GPUs vs. CPUs
• Transforming and rescaling the data
• Loading and visualizing built-in datasets
• Building and loading custom datasets with PyTorch

For a more detailed breakdown of the code, check out the full tutorial on the blog.