Media Summary: Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ... Cruise machine learning platform team worked with Google CMLE team together to enable The hardest part of ML adoption in enterprise is Productization. As we have seen in recent discussions around "ML Ops", there are ...

Distributed Tensorflow Tensorflow Dev Summit - Detailed Analysis & Overview

Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ... Cruise machine learning platform team worked with Google CMLE team together to enable The hardest part of ML adoption in enterprise is Productization. As we have seen in recent discussions around "ML Ops", there are ... Andrew Gasparovic and Jeremiah Harmsen dicuss TF Hub, a new library built to foster the publication, discovery, and ... Sarah Sirajuddin and Andrew Selle discuss Magenta explores the role of ML in the process of creating art and music. This involves developing new deep learning and ...

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Distributed TensorFlow (TensorFlow Dev Summit 2018)
Distributed TensorFlow (TensorFlow Dev Summit 2017)
Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20)
TensorFlow Ecosystem: Integrating TensorFlow with your infrastructure (TensorFlow Dev Summit 2017)
TensorFlow Enterprise (TF Dev Summit '20)
Distributed TensorFlow (TensorFlow @ O’Reilly AI Conference, San Francisco '18)
TensorFlow Enterprise: Productionizing TensorFlow with Google Cloud (TF Dev Summit '20)
TensorFlow Hub (TensorFlow Dev Summit 2018)
TensorFlow Extended (TF Dev Summit '20)
TensorFlow Lite (TensorFlow Dev Summit 2018)
TensorFlow High-Level APIs: Models in a Box (TensorFlow Dev Summit 2017)
Project Magenta (TensorFlow Dev Summit 2018)
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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 ...

Distributed TensorFlow (TensorFlow Dev Summit 2017)

Distributed TensorFlow (TensorFlow Dev Summit 2017)

TensorFlow

Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20)

Distributed TensorFlow model training on Cloud AI Platform (TF Dev Summit '20)

Cruise machine learning platform team worked with Google CMLE team together to enable

TensorFlow Ecosystem: Integrating TensorFlow with your infrastructure (TensorFlow Dev Summit 2017)

TensorFlow Ecosystem: Integrating TensorFlow with your infrastructure (TensorFlow Dev Summit 2017)

Generating input data, running

TensorFlow Enterprise (TF Dev Summit '20)

TensorFlow Enterprise (TF Dev Summit '20)

TensorFlow

Distributed TensorFlow (TensorFlow @ O’Reilly AI Conference, San Francisco '18)

Distributed TensorFlow (TensorFlow @ O’Reilly AI Conference, San Francisco '18)

This talk demonstrates how to perform

TensorFlow Enterprise: Productionizing TensorFlow with Google Cloud (TF Dev Summit '20)

TensorFlow Enterprise: Productionizing TensorFlow with Google Cloud (TF Dev Summit '20)

The hardest part of ML adoption in enterprise is Productization. As we have seen in recent discussions around "ML Ops", there are ...

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 ...

TensorFlow Extended (TF Dev Summit '20)

TensorFlow Extended (TF Dev Summit '20)

TensorFlow

TensorFlow Lite (TensorFlow Dev Summit 2018)

TensorFlow Lite (TensorFlow Dev Summit 2018)

Sarah Sirajuddin and Andrew Selle discuss

TensorFlow High-Level APIs: Models in a Box (TensorFlow Dev Summit 2017)

TensorFlow High-Level APIs: Models in a Box (TensorFlow Dev Summit 2017)

TensorFlow

Project Magenta (TensorFlow Dev Summit 2018)

Project Magenta (TensorFlow Dev Summit 2018)

Magenta explores the role of ML in the process of creating art and music. This involves developing new deep learning and ...

Using the tf.data API to build input pipelines (TensorFlow Meets)

Using the tf.data API to build input pipelines (TensorFlow Meets)

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