Tools for building robust, state-of-the-art machine learning models

In this episode of the Data Exchange I speak with Michael Mahoney, a researcher at UC Berkeley’s RISELab, ICSI, and Department of Statistics. Mike and his collaborators  were recently awarded one of the best papers awards at NeurIPS 2020, one of leading research conferences in machine learning.Subscribe: Apple, Android, Spotify, Stitcher, Google, and RSS.Download the 2021 Trends Report: Data, Machine Learning, AI and learn emerging technologies for data management, data engineering, machine learning, and AI.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.

Om Podcasten

A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].