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Deep Learning

Past Presentations

Semi-Supervised Deep Learning for Climate @ Scale

Climate change is one of the most important problems facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to understand the evolution of the climate system subject to various CO2 emission scenarios. Large scale climate simulations produce 100TB-sized...

Prabhat Data and Analytics Group Lead @NERSC
High-Touch Service @ Scale: Shopping Apps With a Human Face

Personalized content and product recommendations powered by machine learning algorithms are now the bread and butter of shopping apps. As our customers exponentially shift to digital every year, we continuously seek ways to differentiate ourselves in helping customers find the products they...

Natalia Bartol Director, Mobile Engineering @hudsonsbay
Kyla Robinson Director, Product Mobile Apps @hudsonsbay
Deep Learning for Application Performance Optimization

Application performance has direct impact on business and scaling ability. Performance tuning usually involves periodically setting a number of parameters that control run-time environment including CPU, memory, threading, garbage collection, etc. In this session we present our experience and...

Zoran Sevarac Java and Neural Network Expert, Creator @Neuroph, & Founder @DeepNetts
Tackling Computing Challenges @CERN

The Large Hadron Collider (LHC) at CERN is the world's most powerful particle accelerator and is one of the largest and most complicated machines ever built. The LHC has been vital in helping physicists make new discoveries such as the Higgs boson in 2012. Today, the Worldwide LHC Computing...

Maria Girone CTO @CERNopenlab
Getting Started in Deep Learning with TensorFlow 2.0

The introduction of deep learning into the data science toolkit has allowed for significant improvements on many important problems in data science. Many advancements in fields such as natural language processing, computer vision and generative modeling can be attributed to advancements in deep...

Brad Miro Machine Learning Engineer @Google
From Research to Production With PyTorch

PyTorch is a powerful, flexible deep learning platform that enables engineers and researchers to move quickly from research to production. Since the 1.0 release a few months ago, researchers and engineers are already seeing success in taking advantage of the new capabilities to take deep learning...

Jeff Smith Engineering Manager @Facebook AI

Interviews

Jeff Smith Engineering Manager @Facebook AI

From Research to Production With PyTorch

What is the focus of your work today?

I work on PyTorch, which is an open source deep Learning framework developed here at Facebook. I specifically work with the team on a lot of the ways in which we enable the success of a broad open source community that spans both bleeding edge researchers as well as ML product engineers putting deep learning technology to use in...

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