Books
Practical guides to software engineering and data science.
May 2024
From Notebooks to Scalable Systems
This book is a guide for data professionals looking to level up their coding skills. It covers essential skills including testing, object-oriented programming, refactoring, and building APIs. The code examples are in Python, but the principles hold for any programming language. Despite the title, it’s not just for data scientists. It’s a great introduction to anyone looking to get started with software engineering - particularly if you’re working with AI coding agents.
Python Software Engineering
July 2020 · with Hannes Hapke
Automating Model Life Cycles with TensorFlow
This book is a comprehensive guide to deploying machine learning models to production using TensorFlow Extended (TFX). We encourage the standardization of ML model deployment - at the time of writing, this was mostly done with ad hoc code, and many models never made it to production. The technology has moved on, but the introduction in particular is still well worth reading if you want to set up repeatable processes for putting ML models into production.
Machine Learning TensorFlow ML Pipelines TFX
