Anyscale Academy: A Guided Tour of Ray Core

March 2, 2021

This webinar provides a "guided tour" through the core features of Ray.

These features provide a grammar or "pattern language" for building robust, high-performance distributed systems at scale.

We'll focus on Python coding examples – examined in much more detail than in the docs or API reference. For each pattern, we'll look at primary sources, and compare/contrast with how that form of parallelization works in other popular platforms. Then we'll show examples of parallelizing Python code using this – including ways to distribute workloads for other popular Python libraries used in data science work. All of the code is available in Jupyter notebooks on GitHub, and these examples can be run on your laptop.

About Paco Nathan

Known as a "player/coach", with core expertise in data science, natural language, cloud computing; ~40 years tech industry experience, ranging from Bell Labs to early-stage start-ups. Advisor for Amplify Partners, IBM Data Science Community, Recognai, KUNGFU.AI, Primer. Lead committer PyTextRank, kglab. Formerly: Director, Community Evangelism @ Databricks and Apache Spark. Cited in 2015 as one of the Top 30 People in Big Data and Analytics by Innovation Enterprise.

Paco Nathan