In this talk, Xiangrui Meng of Databricks shares his experience in developing MLlib. The talk covers both higher-level APIs, ML pipelines, that make MLlib easy to use, as well as lower-level optimizations that make MLlib scale to massive data sets.
For those unfamiliar with Redis, it is an open source, in-memory data structure server. Originally conceived to solve a problem that required speed and simplicity, it soon became clear that Redis had applications far beyond its original intent. Redis has since grown to include many data structures that resolve very complex programming problems with simple commands executed within the data store.