Description

ODSC team would like to invite you to participate in the FREE ODSC Virtual Panel “Continual learning in practice”

The main goal of the panel is to talk about the benefits of continual learning in data science, especially in today's competitive environment. Our panel of experts will discuss how data evolves, the various architectures that manage Machine Learning models in production, and how these models adapt to shifting data distributions as well as cope with outliers and new tasks. During the panel, you will learn the latest models, advancements, and trends from the top practitioners and would be able to ask questions directly to the speakers.

We will feature 5-6 speakers who will share their expertise on how to apply continual learning to your machine learning models. They will provide key insights and solutions to the challenges presented by adaptive learning and conduct virtual Q&A.

Instructor's Bio

Aric LaBarr, PhD

Associate Professor of Analytics | Institute for Advanced Analytics at NC State University

Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first Master of Science in Analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management. Previously, he was Director and Senior Scientist at Elder Research, where he mentored and led a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government. Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.

Dr. Jon Krohn

 Chief Data Scientist at Untapt, Author of Deep Learning Illustrated

Jon Krohn is Chief Data Scientist at the machine learning company untapt. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University, New York University, and leading industry conferences, as well as online via O'Reilly, the Ai+ Training platform, and the SuperDataScience podcast. Jon holds a PhD from Oxford and has been publishing on machine learning in leading academic journals since 2010; his papers have been cited over a thousand times.

Mihaela van der Schaar, PhD

John Humphrey Plummer Professor of ML, AI, and Medicine at University of Cambridge

Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Fellow at The Alan Turing Institute in London, and a Chancellor’s Professor at UCLA.

Mihaela has received numerous awards. In 2019, she was identified by National Endowment for Science, Technology and the Arts as the most-cited female AI researcher in the UK. She was also elected as a 2019 “Star in Computer Networking and Communications” by N²Women. Mihaela’s research focus is on machine learning, AI and operations research for healthcare and medicine.

Sheamus McGovern 

Software Developer and Ai Expert

Founder of ODSC and Software Architect specializing in, complex multi-platform systems across multiple industries including finance, healthcare, and education.

Anatoli Gorchet, PhD

 CTO and Co-founder of Neurala

Anatoli Gorchet has over 20 years of experience developing massively parallel software for neural computation. He is a pioneer in applying general-purpose computing on graphics processing units to neural modeling. Anatoli has spoken at every major neural network conference as well as at GTC, DARPA, The National Institute for Aerospace and a keynote at the Embedded Systems Conference. He holds several patents, has authored over 30 publications on neural networks, and advises Fortune 500 companies on how to use AI to improve operational efficiencies. He has a PhD in Cognitive and Neural Systems, Boston University; an MS in Computer Science.


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