Experimentation for Engineers av David Sweet

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<B>Optimize the performance of your systems with practical experiments used by engineers in the world’s most competitive industries.</B><BR><BR>In <i>Experimentation for Engineers: From A/B testing to Bayesian optimization</i> you will learn how to:<BR><BR> Design, run, and analyze an A/B test<BR> Break the "feedback loops" caused by periodic retraining of ML models<BR> Increase experimentation rate with multi-armed bandits<BR> Tune multiple parameters experimentally with Bayesian optimization<BR> Clearly define business metrics used for decision-making<BR> Identify and avoid the common pitfalls of experimentation<BR><BR><i>Experimentation for Engineers: From A/B testing to Bayesian</i> optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You’ll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evalu