Hands-On Unsupervised Learning with Python

Descriptive analysis

The first problem to solve in almost any data science scenario concerns understanding its nature. We need to know how the system works or what a dataset is describing. Without this analysis, our knowledge is too limited to make any assumption or hypothesis. For example, we can observe a chart of the average temperature in a city for several years. If we are unable to describe the time series discovering the correlation, seasonalities, and trends, any other question remains unsolved. In our specific context, if we don't discover the similarities between groups of objects, we cannot try to find out a way to summarize their common features. The data scientist has to employ specific tools for every particular problem, but, ...