Hands-On Transfer Learning with Python

Exploratory data analysis

So far, all the initial steps in the project have revolved around business context, requirements, risks, and so on. This is the first touch point where we actually explore in depth the data that is collected/available. EDA helps us understand various facets of our data. In this step, we analyze different attributes of data, uncover interesting insights, and even visualize data on different dimensions to get a better understanding.

This step helps us gather important characteristics of the dataset at hand, which not only is useful in later stages of the project but also helps us identify and/or mitigate potential issues early in the pipeline. We cover an interesting example later on in this chapter for readers to ...