PirateBay Download | sweet d experimentation engineers from b testing meap v8 2022

sweet d experimentation engineers from b testing meap v8 2022

Type:: E-books
Files:: 1
Size:: 5.3 MB
Uploaded On:: Jan. 2, 2023, 3:07 p.m.
Added By:: andryold1
Seeders:: 14
Leechers:: 0
Info Hash:: 12B0866E7C6E8693770E541136BE3D633CA17F31

Textbook in PDF format 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. welcome Optimizing systems by experiment A/B testing: Evaluating a modification to your system Multi-armed bandits: Maximizing business metrics while experimenting Response surface methodology: Optimizing continuous parameters Contextual bandits: Making targeted decisions Bayesian optimization: Automating experimental optimization Managing business metrics Practical considerations Appendix A. Linear regression and the normal equations Appendix B. One factor at a time Appendix C. Gaussian process regression

Get This Torrent

Sweet D. Experimentation for Engineers. From A-B testing...(MEAP v8) 2022.pdf 5.3 MB

Details for: Sweet D. Experimentation for Engineers. From A-B testing...(MEAP v8) 2022

sweet d experimentation engineers from b testing meap v8 2022

Similar Posts: