Opportunities in Deep Learning: Commercialization and Career paths

#deeplearning #dl #dlcareer
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Deep learning has become the new norm for a wide range of video analysis tasks, ranging from simple classification to synthesizing realistic new videos from text inputs. Keeping up with state-of-the-art DL algorithms has never been harder. Even the 'Transformer' has been given a new meaning. This presentation will uncover the mystery of deep learning in plain language and explain how those algorithms are deployed to products. More importantly, the audience will learn what it takes to become a deep learning engineer.

The presentation will cover the following topics:

- Recent advances in deep learning and self-supervised learning (video classification).

- How are deep learning algorithms commercialized?

- Career roadmap for aspirant candidates



  Date and Time

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  • Date: 24 Nov 2022
  • Time: 06:00 PM to 08:00 PM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
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  • Starts 05 October 2022 06:02 PM
  • Ends 23 November 2022 05:00 PM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
  • No Admission Charge


  Speakers

Dr. Peng Dai Dr. Peng Dai

Topic:

Opportunities in Deep Learning: Commercialization and Career Paths

Biography:

Dr Peng Dai is a Staff Scientist at Huawei Technologies Canada. He has contributed to a number of high impact products. He obtained his B.Eng and M.Eng degrees in Electrical Engineering from Tianjin University in 2006 and 2008, respectively and PhD degree from School of Electrical & Electronic Engineering, Nanyang Technological University. Dr Dai’s research goals are directed towards artificial intelligence for video understanding. In particular, his recent projects primarily focus on data efficient deep learning, including self-supervised learning, few shot learning, and multimodality fusion. He has authored more than 50 publications in top AI conferences and journals.

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