Hands-On Transfer Learning with Python

Data understanding

Data collection and understanding is the second step in the CRISP-DM framework. In this step we take a deeper dive to understand and analyze the data for the problem statement formalized in the previous step. This step begins with investigating the various sources of data outlined in the detailed project plan previously. These sources of data are then used to collect data, analyze different attributes, and make a note of data quality. This step also involves what is generally termed as exploratory data analysis.

Exploratory data analysis (EDA) is a very important sub-step. It is during EDA we analyze different attributes of data, their properties and characteristics. We also visualize data during EDA for a better understanding ...