AutoML is a machine learning technique that has grown in popularity over the last 2 years. This month we take a look at this topic from a few different angles.
Planned Talks :
"AutoML on GCP" - Sam Witteveen
Recently at Google's Cloud Next event, Google announced a new suite of AutoML products which allow for making very high-quality ML models for Vision, Text and Tabular data. Sam will show you where these can be useful and how to get started using the AutoML service.
"AutoML with Autokeras" - Timothy Liu
AutoML is gaining popularity of the launch of various cloud services all claiming to enable state of the art ML without the need to hand-craft models. In this talk, Timothy will be sharing on the concept of AutoML, and how to use a library like Autokeras to get started with AutoML without the use of proprietary services.
"Single-Path Neural Architecture Search (and the Lottery Ticket Hypothesis)" - Martin Andrews
Martin will dive into two interesting recent papers, one with a more efficient way to do AutoML, and the other with insights into Neural Network training, pruning and initialisation (in that order).
"OpenAI DOTA Five Finals" - Olzhas Akpambetov
Olzhas will explain the main ideas of Proximal Policy Optimization (PPO) and will include an overview of the OpenAI Five Finals event he attended on April 13 in San Francisco where OpenAI's system, developed with a scaled version of PPO, played against the 2018 DOTA 2 world champions "OG".
