Future Industrial Operations with Machine Learning

Oct 11, 07:00 PM PDT
  • Virtual AICamp
  • 160 RSVP
This talk will discuss decision making for industrial operations with Self-Supervised Learning (SSL) and Reinforcement Learning (RL). Self-supervised learning holds a lot of promise to build robust machine learning models without massive amounts of labelled data. Reinforcement learning presents a formal framework for sequential decision-making. Thanks to the recent success of deep neural networks, research into both SSL and RL has enjoyed remarkable achievements.
This talk will briefly share our journey on using SSL and RL to automate and optimise industrial operations. It will also highlight some prescriptive guidance on accelerating production-ready machine learning pipelines on AWS.

We will give away a few AWS credits during the event.

Chen Wu (AWS)

Chen Wu is a senior data scientist at AWS. Chen works directly with AWS customers to deliver end-to-end data science solutions. Chen is passionate about making positive impacts on multiple verticals such as mining, automotive, transportation, and manufacturing through machine learning. Prior to joining AWS, Chen worked in the field of data-intensive astronomy and high performance computing.
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