Ameet Talwalkar, Assistant Professor of Computer Science, UCLA @ MLconf SF Part 2

Apache Spark’s MLlib is a terrific library for fitting large-scale machine learning models. However, translating high-level problem statements like “learn a classifier” into a working model presently requires significant manual effort (via ad hoc parameter tuning) and computational resources (to fit several models). We present our work on the MLbase optimizer – a system designed on top of Spark to quickly and automatically search through a hyperparameter space and find a good model. By leveraging performance enhancements, better search algorithms, and statistical heuristics, our system offers an order of magnitude speedup over standard methods.

Видео Ameet Talwalkar, Assistant Professor of Computer Science, UCLA @ MLconf SF Part 2 автора Seeds of Success