My personal reading list for October, November, and December 2022.
Color Key: Special Notes, Completed Reading. Updated throughout the Quarter.
At Bat (Schnell)
AWS Certified Database - Specialty (DBS-C01) Certification, by Kate Gawron, Packt Publishing, 2022. Copy provided by Packt publicist Nivedita Singh.
The Ideal Executive: Why You Cannot Be One and What to Do About It, by Ichak Kalderon, The Adizes Institute, 2004.
At Bat (Langsam)
Machine Learning Engineering in Action, by Ben Wilson, Manning, 2022. Copy provided by author Ben Wilson.
The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page, Basic Books, 2018.
Practical Statistics for Data Scientists: 50 Essential Concepts, by Peter Bruce and Andrew Bruce, O'Reilly, 2017. Copy provided by MarkLogic.
On Deck
Fluent Python: Clear, Concise, and Effective Programming, by Luciano Ramalho, O'Reilly, 2015.
The Manager's Path: A Guide for Tech Leaders Navigating Growth and Change, by Camille Fournier, O'Reilly, 2017.
The Staff Engineer's Path: A Guide for Individual Contributors Navigating Growth and Change, by Tanya Reilly, O'Reilly, 2022.
In the Hole
97 Things Every Data Engineer Should Know, edited by Tobias Macey, O'Reilly, 2021. Copy provided by Promethium.
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable (Second Edition), by Christoph Molnar, Independently Published, 2022.