Daniel Tunkelang talks about what search looks like when viewed through a query understanding mindset. He focuses on query performance prediction, query rewriting, and search suggestions.
Aish Fenton discusses Netflix' machine learning algorithms, including distributed Neural Networks on AWS GPUs, providing insight into offline experimentation and online AB testing.
Nellwyn Thomas discusses how Etsy is using A/B testing, how Etsy's data-driven culture has evolved over time and how continuous delivery and big data can coexist.
Andrea Burbank discusses the evolution of Pinterest's A/B testing platform and how one can learn from their mistakes to go from simply running experiments to actually deriving insights.
Danielle Jabin shares some of Spotify's key takeaways from their A/B testing efforts and the challenges they faced in building out their A/B testing infrastructure.
Wil Stuckey explains how Etsy manages to deploy nearly ~10,000 changes in one year, and how they run A/B experiments in the midst of continual code change.