Personal Reading List: 1Q2020
My personal reading list for January, February, and March 2020.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
How to Make Mistakes in Python, by Mike Pirnat, O'Reilly, 2015. Copy provided by O'Reilly.
The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018.
Rethinking Strategy, by Steve Tighe, Wiley, 2019. Copy provided by author Steve Tighe.
At Bat (Langsam)
Fluent Python: Clear, Concise, and Effective Programming, by Luciano Ramalho, O'Reilly, 2015.
Practical Statistics for Data Scientists: 50 Essential Concepts, by Peter Bruce and Andrew Bruce, O'Reilly, 2017. Copy provided by MarkLogic.
On Deck
Serving Machine Learning Models, by Boris Lublinsky, O'Reilly, 2017. Copy provided by Lightbend.
What is Augmented Analytics?: Powering Your Data with AI, by Alice LaPlante, O'Reilly, 2019. Copy provided by Oracle.
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.