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Monday, October 26, 2020

Upcoming ACM Talk: Deep Learning and Software Engineering

Plan to attend this ACM talk:

VIP Reminder: Nov 2 Talk with fast.ai http://fast.ai/  Co-Founder Jeremy Howard on Applying Software Engineering Practices to Deep Learning... 

If you haven't done so already, Register now  for the next free ACM TechTalk, "It's Time Deep Learning Learned from Software Engineering," presented on Monday, November 2, at 1:00 PM ET/10:00 AM PT by Jeremy Howard, Founding Researcher at fast.ai and Distinguished Research Scientist at the University of San Francisco. Hamel Husain, Staff Machine Learning Engineer at GitHub, will moderate the questions and answers session following the talk.

Leave your comments and questions with our speaker now and any time before the live event on ACM's Discourse Page. And check out the page after the webcast for extended discussion with your peers in the computing community, as well as further resources on fastai and deep learning.

(If you'd like to attend but can't make it to the virtual event, you still need to register to receive a recording of the TechTalk when it becomes available.)

Note: You can stream this and all ACM TechTalks on your mobile device, including smartphones and tablets.

The world of deep learning has traditionally been an academic world, drawing from mathematics, statistics, and operations research. This has meant great advances in the development of theory and algorithms, but software engineering best practices have sometimes been left behind. In this talk, the creator of fastai will explain how bringing software engineering best practices, such as layered API design and decoupling, have allowed him to provide a deep learning library that is both easier to use for beginners, at the same time as being more deeply hackable for experts, and also increasing performance. He will be drawing from research discussed in the peer reviewed paper describing the principles of fastai.

Presenter:  Jeremy Howard, Founding Researcher, fast.ai; Distinguished Research Scientist, University of San Francisco

Jeremy Howard is a data scientist, researcher, developer, educator, and entrepreneur. Jeremy is a founding researcher at fast.ai, a research institute dedicated to making deep learning more accessible. He is also a Distinguished Research Scientist at the University of San Francisco, the chair of WAMRI, and is Chief Scientist at platform.ai.  http://fast.ai/ 

Previously, Jeremy was the founding CEO of Enlitic, which was the first company to apply deep learning to medicine, and was selected as one of the world’s top 50 smartest companies by MIT Tech Review two years running. He was the President and Chief Scientist of the data science platform Kaggle .... Before that, he spent eight years in management consulting, at McKinsey & Co, and AT Kearney. Jeremy has invested in, mentored, and advised many startups, and contributed to many open source projects. ....

Moderator:  Hamel Husain, Staff Machine Learning Engineer, GitHub

Hamel Husain is a Staff Machine Learning Engineer at GitHub, and is focused on creating developer tools powered by machine learning.  .... .

Hamel holds a Bachelors degree in Management Science and Mathematics from Southern Methodist University, as well as a Masters of Computer Science from Georgia Tech. You can read more about Hamel's recent work on his page: https://hamel.dev.

Visit learning.acm.org/techtalks-archive for our full archive of past TechTalks  ... 

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