Hands-On Unsupervised Learning with Python

Why do we need machine learning?

Data is everywhere. At this very moment, thousands of systems are collecting records that make up the history of specific services, together with logs, user interactions, and many other context-dependent elements. Only a decade ago, most companies couldn't even manage 1% of their data efficiently. For this reason, databases were periodically pruned and only important data used to be retained in permanent storage servers.

Conversely, nowadays almost every company can exploit cloud infrastructures that scale in order to cope with the increasing volume of incoming data. Tools such as Apache Hadoop or Apache Spark allow both data scientists and engineers to implement complex pipelines involving extremely large ...