IEEE Computer Society Chicago: Navigating the Complexity of ML Production: Insights and Lessons Learned
For our IEEE Computer Society Chicago April meeting, we have an invited speaker from Standard AI talking about Navigating the Complexity of ML Production: Insights and Lessons Learned. This talk will be co-hosted by ACM Chicago. Details to this event and registration are below.
Date and Time
Location
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Registration
- Date: 05 Apr 2023
- Time: 06:00 PM to 07:00 PM
- All times are (UTC-05:00) Central Time (US & Canada)
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- Co-sponsored by ACM Chicago
Speakers
Atul Dhingra of Standard AI
Navigating the Complexity of ML Production: Insights and Lessons Learned
Our April 5th Speaker, Atul Dhingra, will present his insights into the Machine Learning (ML) model lifecycle in production. The talk covers various aspects of ML Operations that go into making a successful model deployment, from the inception of a problem to making it production ready.
The talk will also discuss closing the loop between data distribution drift between training and inference time. By the end of the talk, the audience will gain useful insights into how to scale and accelerate the velocity of large production models in a cost-effective way.
Biography:
Atul Dhingra is an Engineering Manager at Standard AI where he works on autonomous checkout powered by Computer Vision and AI.
He has a combined experience of over 10 years in industry and academia working on advanced Machine Learning and Deep Learning algorithms to solve complex problems in the domain of Autonomous checkout, autonomous vehicles, and Biometrics.
He has played a vital role in building large-scale cutting-edge machine-learning production systems.
Address:United States
Agenda
All times in CDT:
6:00 to 6:05 PM - Introduction
6:05 to 6:40 PM - Talk
6:40 to 6:55 PM - Q&A
6:55 to 7:00 PM - Closing and Adjournment