My personal reading list for October, November, and December 2019.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018.
What is Augmented Analytics?: Powering Your Data with AI, by Alice LaPlante, O'Reilly, 2019. Copy provided by Oracle.
At Bat (Langsam)
Practical Statistics for Data Scientists: 50 Essential Concepts, by Peter Bruce and Andrew Bruce, O'Reilly, 2017. Copy provided by MarkLogic.
Fluent Python: Clear, Concise, and Effective Programming, by Luciano Ramalho, O'Reilly, 2015.
On Deck
Thinking Architecturally: Lead Technical Change Within Your Engineering Team, by Nathaniel Schutta, O'Reilly, 2018. Copy provided by Pivotal.
In the Hole
Getting DataOps Right, by Andy Palmer, Michael Stonebraker, Nik Bates-Haus, Liam Cleary, and Mark Marinelli, O'Reilly, 2019. Copy provided by Tamr.
Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith, by Sam Newman, O'Reilly, 2020. Copy provided by Nginx.