{"product_id":"engineering-online-experimentation-and-ml-evaluations-von-ming-lei","title":"Engineering Online Experimentation and ML Evaluations","description":"\n                                \n                \u003cp\u003eOnline experimentation is now essential for modern software and machine learning teams. This book provides an engineer-first, end-to-end guide to building and operating production-ready experimentation platforms.\u003c\/p\u003e\n                                \n                \n                \u003cp\u003eThe book begins with Part I establishing the core foundations of credible experimentation, including hypothesis testing, power analysis, sample sizing, metric design, and common pitfalls such as peeking, multiple testing, and novelty or learning effects. Part II focuses on platform engineering—traffic and identity management, mutual exclusion, event and logging design, ETL\/ELT pipelines, building a stats engine with SciPy and statsmodels, SRM detection, integrating deployments with feature flags and canaries, and setting up guardrail and health monitoring. Part III presents advanced designs that improve speed and sensitivity: sequential testing with alpha spending, bootstrap intervals for ratios and quantiles, A\/B\/n testing with ANOVA, interleaving for ranking systems, switchback and geo experiments, and multi-armed bandits. Part IV connects experimentation to ML workflows, covering offline, shadow, canary, and A\/B evaluation pipelines; Bayesian optimization for adaptive experimentation; counterfactual and IPS methods for learning from logs; and safe retraining supported by strong governance.\u003c\/p\u003e\n                                \n                \n                \u003cp\u003eWhat you will learn:\u003c\/p\u003e\n                                \n                \n                \u003cul\u003e\n                                        \n                    \n                    \u003cli\u003eDesign trustworthy experiments with proper metrics, guardrails, α\/power\/MDE settings, and safeguards against peeking and multiple-testing errors\u003c\/li\u003e\n                                        \n                    \n                    \u003cli\u003eBuild a production-ready experimentation stack with assignment, identity\/diversion, logging, ETL\/ELT, a stats engine, and SRM checks\u003c\/li\u003e\n                                        \n                    \n                    \u003cli\u003eRun advanced designs at scale, including sequential tests, bootstrap CIs, interleaving, switchback\/geo experiments, and multi-armed bandits\u003c\/li\u003e\n                                        \n                    \n                    \u003cli\u003eEvaluate ML systems from offline to online, leverage experiment logs for learning, and enable safe retraining with governance\u003c\/li\u003e\n                                        \n                \n                \u003c\/ul\u003e\n                                \n                \n                \u003cp\u003eWho this book is for:\u003c\/p\u003e\n                                \n                \n                \u003cp\u003eThe primary audience for this book includes Data Engineers, ML Engineers, and Platform or Software Architects. It is also well suited for Product and Data Scientists who want a deeper understanding of experimentation systems and the engineering principles behind them.\u003c\/p\u003e\n                            \n            \u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9798868827204\"\u003e\u003ch3\u003eArchitecture, Statistics and Machine Learning for Production-Scale Systems\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9798868827204","offer_id":57323050729797,"sku":"9798868827204","price":64.19,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/993189f6-6819-48a0-b13d-2076e5e735b6.jpg?v=1780120076","url":"https:\/\/shop.autorenwelt.de\/products\/engineering-online-experimentation-and-ml-evaluations-von-ming-lei","provider":"Autorenwelt Shop","version":"1.0","type":"link"}