With the subtitle "From A/B testing to Bayesian optimization", this book consists of a toolbox of techniques for evaluating new features and fine-tuning parameters. David Sweet starts with a deep dive into methods like A/B testing, and then graduates to advanced techniques used to measure performance in industries such as finance and social media. He shows how to evaluate the changes you make to your system and ensure that your testing doesn’t undermine revenue or other business metrics.

<ASIN:‎1617298158>

Author: David Sweet
Publisher: Manning
Date: March 2023
Pages: 248
ISBN: 978-1617298158
Print: 1617298158
Kindle: B0BSVHBFK2
Audience: General
Level: Intermediate
Category: Theory & Techniques 

Topics include:

• Design, run, and analyze an A/B test
• Break the "feedback loops" caused by periodic retraining of ML models
• Increase experimentation rate with multi-armed bandits
• Tune multiple parameters experimentally with Bayesian optimization
• Clearly define business metrics used for decision-making
• Identify and avoid the common pitfalls of experimentation

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