chapter eight
8 Getting started with deep learning with tabular data
This chapter covers
- Introduction to the deep learning with tabular data stacks - low-level frameworks and high-level application programming interfaces (APIs) for deep learning
- The PyTorch with fastai stack
- The PyTorch with TabNet stack
- The PyTorch with Lightning Flash stack
- Description of the stacks we didn’t exercise and why we didn’t exercise them
- Comparison of the pros and cons of the deep learning with tabular data stacks
In the preceding four chapters (chapters 4 to 7), we have focused on machine learning with tabular data, that is, non-deep learning approaches to dealing with tabular data. This set of chapters culminated in chapter 7 where we went through an end-to-end example of applying a gradient boosting approach to the Kuala Lumpur real estate tabular dataset. For the next three chapters we will focus on deep learning approaches to tabular data, starting with the examination of deep learning with tabular data stacks in this chapter.