Published in 2018 and now available as an open-access text, Machine Learning for Data Streams is a great guide for "data stream mining and real-time analytics." The book is authored by a group of computer science experts, Albert Bifet (Telecom Paris Tech, France), Ricard Gavalda (Politecnica de Catalunya, Barcelona), Geoff Holmes (University of Waikato, Hamilton, New Zealand) and Bernhard Pfahringer (University of Auckland, New Zealand). Their expertise shows in this practical, hands-on reference manual. To view the contents, navigate to the Open Access tab and click the "View HTML" section. Here, readers will find an introduction to big data and analytics, tools and methodologies for data stream mining, and several different tutorials on the MOA (Massive Online Analysis) framework. Readers looking for information on a particular subject within data and analytics will want to check out the Index, which embeds links to appropriate pages. Plus, a bonus of this online format is that it allows readers with their own subject-matter expertise to post comments (note that they will need to be approved by an administrator before they become public-facing).