Exploring and understanding the dataset

Before diving into the machine learning implementation, it's necessary to analyze the data that is available for our use case. Since machine learning training is based on examples, we need to clearly understand what data to consider and check the quality of the available records.

Tip

Data scientists and business analysts spend a lot of time and resources getting a clear understanding of the datasets, checking their quality, and preparing them. Although these operations don't seem to be directly linked to the realization of a machine learning algorithm, they are essential if you wish to get solid results. The actual training of the model is the last mile of a longer journey that begins with comprehending data, the control of its quality, and preparing it.

Let's start by getting a clear understanding of the information that we have in our dataset to build our use case.

Understanding the data

To have a clear understanding...