Working with MXNet and Visualizing Datasets – Gluon and DataLoader
In the previous chapter, we learned how to set up MXNet. We also verified how MXNet could leverage our hardware to provide maximum performance. Before applying deep learning (DL) to solve specific problems, we need to understand how to load, manage, and visualize the datasets we will be working with. In this chapter, we will start using MXNet to analyze some toy datasets in the domains of numerical regression, data classification, image classification, and text classification. To manage those tasks efficiently, we will see new MXNet libraries and functions such as Gluon (an API for DL) and DataLoader.
In this chapter, we will cover the following topics:
- Understanding regression datasets – loading, managing, and visualizing the House Sales dataset
- Understanding classification datasets – loading, managing, and visualizing the Iris dataset
- Understanding image datasets – loading...
