Media Summary: Brennan Saeta walks through how to optimize Chris Lattner and Richard Wei unveil Swift for Andrew Gasparovic and Jeremiah Harmsen dicuss TF Hub, a new library built to foster the publication, discovery, and ...

Training Performance A User S Guide To Converge Faster Tensorflow Dev Summit 2018 - Detailed Analysis & Overview

Brennan Saeta walks through how to optimize Chris Lattner and Richard Wei unveil Swift for Andrew Gasparovic and Jeremiah Harmsen dicuss TF Hub, a new library built to foster the publication, discovery, and ... Derek Murray discusses tf.data, the recommended API for building input pipelines in Sarah Sirajuddin and Andrew Selle discuss Edd Wilder-James announces a new set of mailing lists to help communication and coordination, the expansion of the SIG ...

Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ... Alex Passos discusses Eager Execution, which provides a simpler, more intuitive interface to We have seen tremendous advances in many different areas of machine learning. The use of

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Training Performance: A user’s guide to converge faster (TensorFlow Dev Summit 2018)
TensorFlow Dev Summit 2018 - Livestream
Keynote (TensorFlow Dev Summit 2018)
Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)
Debugging TensorFlow with TensorBoard plugins (TensorFlow Dev Summit 2018)
TensorFlow Hub (TensorFlow Dev Summit 2018)
tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)
Machine Learning in JavaScript (TensorFlow Dev Summit 2018)
TensorFlow Lite (TensorFlow Dev Summit 2018)
Open Source Collaboration (TensorFlow Dev Summit 2018)
Distributed TensorFlow (TensorFlow Dev Summit 2018)
Eager Execution (TensorFlow Dev Summit 2018)
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Training Performance: A user’s guide to converge faster (TensorFlow Dev Summit 2018)

Training Performance: A user’s guide to converge faster (TensorFlow Dev Summit 2018)

Brennan Saeta walks through how to optimize

TensorFlow Dev Summit 2018 - Livestream

TensorFlow Dev Summit 2018 - Livestream

TensorFlow Dev Summit 2018

Sponsored
Keynote (TensorFlow Dev Summit 2018)

Keynote (TensorFlow Dev Summit 2018)

TensorFlow Dev Summit 2018

Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)

Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)

Chris Lattner and Richard Wei unveil Swift for

Debugging TensorFlow with TensorBoard plugins (TensorFlow Dev Summit 2018)

Debugging TensorFlow with TensorBoard plugins (TensorFlow Dev Summit 2018)

Watch this demo of the

Sponsored
TensorFlow Hub (TensorFlow Dev Summit 2018)

TensorFlow Hub (TensorFlow Dev Summit 2018)

Andrew Gasparovic and Jeremiah Harmsen dicuss TF Hub, a new library built to foster the publication, discovery, and ...

tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)

tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)

Derek Murray discusses tf.data, the recommended API for building input pipelines in

Machine Learning in JavaScript (TensorFlow Dev Summit 2018)

Machine Learning in JavaScript (TensorFlow Dev Summit 2018)

Nikhil Thorat and Daniel Smilkov discuss

TensorFlow Lite (TensorFlow Dev Summit 2018)

TensorFlow Lite (TensorFlow Dev Summit 2018)

Sarah Sirajuddin and Andrew Selle discuss

Open Source Collaboration (TensorFlow Dev Summit 2018)

Open Source Collaboration (TensorFlow Dev Summit 2018)

Edd Wilder-James announces a new set of mailing lists to help communication and coordination, the expansion of the SIG ...

Distributed TensorFlow (TensorFlow Dev Summit 2018)

Distributed TensorFlow (TensorFlow Dev Summit 2018)

Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ...

Eager Execution (TensorFlow Dev Summit 2018)

Eager Execution (TensorFlow Dev Summit 2018)

Alex Passos discusses Eager Execution, which provides a simpler, more intuitive interface to

TensorFlow Dev Summit 2018 Highlights

TensorFlow Dev Summit 2018 Highlights

We have seen tremendous advances in many different areas of machine learning. The use of