Experimentation for Engineers: From A/B testing to Bayesian optimization (MEAP v8)КНИГИ » ПРОГРАММИНГ
Название: Experimentation for Engineers: From A/B testing to Bayesian optimization (MEAP v8) Автор: David Sweet Издательство: Manning Publications Год: 2022 Страниц: 326 Язык: английский Формат: pdf, epub Размер: 10.2 MB
Learn practical and modern experimental methods used by engineers in technology and trading.
In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to
Design, run, and analyze an A/B test Break the "feedback loops" cause 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
Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox for optimizing machine learning systems, quantitative trading strategies, and more. You’ll start with a deep dive into tests like A/B testing, and then graduate to advanced techniques used to measure performance in highly competitive industries like finance and social media. The tests in this unique, practical guide will quickly reveal which approaches and features deliver real results for your business.
about the technology Tuning your systems is best done by following established methods employed by high-performing teams like the ones led by author David Sweet. This book reveals experiments, tests, metrics, and industry-tested tools that will ensure your projects are constantly improving, delivering revenue, and ensuring user satisfaction.
about the book Experimentation for Engineers: From A/B testing to Bayesian optimization teaches you reliable techniques for evaluating new features and fine-tuning parameters. You’ll learn to optimize production systems with methods that have been proven in highly competitive environments. Each method is fully explained using basic math and Python code, and illustrated with real-world use cases in quantitative trading, recommender systems, and ad serving.
You’ll learn how to evaluate the changes you make to your system and ensure that your testing doesn’t undermine revenue or other business metrics. By the time you’re done, you’ll be able to seamlessly deploy experiments in production while avoiding common pitfalls.
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Experimentation for Engineers: From A/B testing to Bayesian optimization (MEAP v8) 
Название: Experimentation for Engineers: From A/B testing to Bayesian optimization (MEAP v8)
