Experimentation for Engineers: From A/B Testing to Bayesian Optimization

Learn practical and modern experimental methods used by engineers in technology and trading.

Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of methods for optimizing machine learning systems, quantitative trading strategies, and more. You'll start with a deep dive into A/B testing, and then graduate to advanced methods used to improve performance in highly competitive industries like finance and social media. The experimentation skills you'll master in this unique, practical guide will quickly reveal which approaches and features deliver real results for your business.

In Experimentation for Engineers, you'll learn how to evaluate the changes you make to your system and ensure that your experiments don't undermine revenue or other business metrics. By the time you're done, you'll be able to seamlessly deploy changes to production while avoiding common pitfalls.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

學習工程師在科技和交易中使用的實用和現代實驗方法。

《工程師的實驗：從A/B測試到貝葉斯優化》是一個優化機器學習系統、量化交易策略等方法的工具箱。您將從深入研究A/B測試開始，然後進一步探索在金融和社交媒體等高競爭行業中提高性能的高級方法。這本獨特而實用的指南將使您掌握實驗技能，快速發現哪些方法和功能能為您的業務帶來實際效果。

在《工程師的實驗》中，您將學習如何評估對系統所做的更改，確保您的實驗不會損害收入或其他業務指標。完成後，您將能夠無縫地將更改部署到生產環境，同時避免常見的陷阱。

購買印刷版書籍將包含Manning Publications提供的PDF、Kindle和ePub格式的免費電子書。

David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram, where he used experimental methods to tune trading systems and recommender systems. This book is an extension of his lectures on tuning quantitative trading systems given at NYU Stern over the past three years.

David Sweet曾在GETCO擔任量化交易員，並在Instagram擔任機器學習工程師，他在這裡使用實驗方法來調整交易系統和推薦系統。這本書是他在過去三年在紐約大學斯特恩商學院所講授的調整量化交易系統的講座的延伸。