Jeremy Howard
fastai and USF
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Sylvain Gugger
fastai
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THIS LECTURE WILL BE PRESENTED LIVE
fastai is a deep learning library which provides practitioners with
high-level components that can quickly and easily provide state-of-the-art
results in standard deep learning domains, and provides researchers
with low-level components that can be mixed and matched to build new
approaches. It aims to do both things without substantial compromises
in ease of use, flexibility, or performance. This is possible thanks
to a carefully layered architecture, which expresses common underlying
patterns of many deep learning and data processing techniques in terms
of decoupled abstractions. These abstractions can be expressed concisely
and clearly by leveraging the dynamism of the underlying Python language
and the flexibility of the PyTorch library. fastai includes: a new type
dispatch system for Python along with a semantic type hierarchy for
tensors; a GPU-optimized computer vision library which can be extended in
pure Python; an optimizer which refactors out the common functionality of
modern optimizers into two basic pieces, allowing optimization algorithms
to be implemented in 4-5 lines of code; a novel 2-way callback system
that can access any part of the data, model, or optimizer and change it
at any point during training; a new data block API; and much more. We
have used this library to successfully create a complete deep learning
course, which we were able to write more quickly than using previous
approaches, and the code was more clear. The library is already in wide
use in research, industry, and teaching.
Video:
To access the live webcast of the talk (active at 16:28 of the day of the
presentation) and the archived version of the talk, use the URL
SU-EE380-20200219.
This is a
first class reference and can be transmitted by email, Twitter, etc.
A URL referencing a YouTube view of the lecture will be posted
HERE
a week or so following the presentation.
About the Speakers:
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Jeremy Howard is an entrepreneur, business strategist, developer, and
educator. Jeremy is a founding researcher at fast.ai, a research institute
dedicated to making deep learning more accessible. He is also a faculty
member at the University of San Francisco, and is Chief Scientist at
doc.ai and platform.ai.
Previously, Jeremy was the founding CEO 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, where he was the top ranked participant in international
machine learning competitions 2 years running. He was the founding CEO
of two successful Australian startups (FastMail, and Optimal Decisions
Group--purchased by Lexis-Nexis). Before that, he spent 8 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.
He has many television and other video appearances, including as a
regular guest on Australia's highest-rated breakfast news program, a
popular talk on TED.com, and data science and web development tutorials
and discussions.
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Sylvain's research at fast.ai has focused on designing and improving
techniques that allow models to train fast with limited resources. He
has also been a core developer of the fastai library, including
implementing the warping transformations, the preprocessing pipeline,
much of fastai.text, and a lot more.
Prior to fastai, Sylvain was a Mathematics and Computer Science teacher
in Paris for seven years. He taught CPGE, the 2-year French program that
prepares students for graduate programs at France's top engineering
schools (the "grandes écoles"). After relocating to the USA in 2015,
Sylvain wrote ten textbooks covering the entire CPGE curriculum. Sylvain
is an alumni from École Normale Supérieure (Paris, France)
and has
a Master's Degree in Mathematics from University Paris XI (Orsay,
France). He lives in Brooklyn with his husband and two sons.
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