Lessons in Google Search data

Acme Corporation is a global leader in commerce marketing. Manu Mukerji walks you through Acme Corporation's machine learning example for universal catalogs, explaining how the training and test sets are generated and annotated; how the model is pushed to production, automatically evaluated, and used; production issues that arise when applying ML at scale in production; lessons learned; and more.

Apache Beam equips users with a novel programming model in which the classic batch/streaming data processing dichotomy is erased. Eugene Kirpichov details the modularity and composability advantages created by treating data ingestion as just another data processing task and walks you through building highly modular data ingestion APIs using the new Beam programming model primitive Splittable DoFn.

The Google Brain team conducts research on difficult problems in artificial intelligence and builds large-scale computer systems for machine learning research, both of which have been applied to dozens of Google products. Jeff Dean highlights some of Google Brain's projects with an eye toward how they can be used to solve challenging problems.

Power Poetry is the largest online platform for young poets, with over 350K users. Ann Nguyen explains how Power Poetry is extending the learning potential with machine learning and covers the technical elements of the Poetry Genome, a series of ML tools to analyze and break down similarity scores of the poems added to the site.

William Vambenepe explains how a pivot toward machine learning and artificial intelligence has created clearer separation among clouds than ever before. William walks you through an interesting use case of machine learning in action and discusses the central role AI will play in big data analysis moving forward.

Jago Macleod shares recent work that allows users to extend the Kubernetes API with custom resources and controllers and leverage this pattern. Its growing popularity in Kubernetes and other projects in the space suggests you will see more of it in the future.