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On demand: The 2021 AWS Machine Learning Summit

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Amazon Web Services (AWS) held a free virtual Machine Learning Summit on June 2, with the goal of bringing together customers, developers, and the science community to learn about advances in the practice of machine learning (ML).

Opening keynote

The event began with a keynote from from Swami Sivasubramanian, AWS vice president of machine learning; Bratin Saha, vice president of AWS Machine Learning Services; and Yoelle Maarek, vice president of research science, Alexa Shopping.

AWS ML Summit 2021 | Opening Keynote

Fireside chat

Next up was a fireside chat. Andrew Ng, founder and CEO of Landing AI, and Sivasubramanian discussed the future of ML, the skills that are fundamental for the next generation of ML practitioners, and how to bridge the proof-of-concept-to-production gap in ML.

AWS ML Summit 2021 | Fireside Chat

Breakout sessions

The Summit included four audience-focused tracks which ran throughout the day:

  • Science of Machine Learning;
  • Impact of Machine Learning;
  • How Machine Learning Is Done; and
  • Machine Learning — No Experience Required

Science of Machine Learning track fireside chat

The Science of Machine Learning track comprised six 30-minute presentations, and a fireside chat on deep learning and language with Amazon distinguished scientists Alex Smola and Bernhard Schölkopf, and Alexa AI senior principal scientist Dilek Hakkani-Tur.

Machine Learning track fireside chat replay: Causality, robustness, and natural language understanding in ML

Science of Machine Learning track session videos and interviews

Below are video replays from each of the speakers in the Science of Machine Learning track, along with links to interviews Amazon Science did with each of the speakers in the weeks before the summit. Click here to see the full list of ML Summit videos.

Marzia Polito replay: Building high-quality computer vision models using only a few examples

Michael Kearns replay: The ethical algorithm

Philip Resnik replay: Analyzing social media for suicide risk using natural language processing

Ryan Tibshirani replay: COVIDcast: An ecosystem for COVID-19 tracking and forecasting

Kathleen McKeown replay: Towards controllable language generation

George Karypis replay: Deep Graph Library: Deep Graph learning at scale



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