About this episode
David Sweet, author of “Tuning Up: From A/B testing to Bayesian optimization”, introduces Dan and Chris to system tuning, and takes them from A/B testing to response surface methodology, contextual bandit, and finally bayesian optimization. Along the way, we get fascinating insights into recommender systems and high-frequency trading! Join the discussion Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today! Sponsors: O'Reilly Media – Learn by doing — Python, data, AI, machine learning, Kubernetes, Docker, and more. Just open your browser and dive in. Learn more and keep your teams’ skills sharp at oreilly.com/changelog RudderStack – Smart customer data pipeline made for developers. RudderStack is the smart customer data pipeline. Connect your whole customer data stack. Warehouse-first, open source Segment alternative. Changelog++ – You love our content and you want to take it to the next level by showing your support. We’ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Let’s do this ! Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com . Featuring: David Sweet – LinkedIn , X Chris Benson – Website , GitHub , LinkedIn , X Daniel Whitenack – Website , GitHub , X Show Notes: Books “Experimentation for Engineers” by David Sweet Tuning Up | GitHub Manning 40% discount code: podpracticalAI19 Something missing or broken? PRs welcome!