Responsible AI with TensorFlow

Responsible AI with TensorFlow

Introducing a framework to think about ML, fairness and privacy. This talk will propose a fairness-aware ML workflow, illustrate how TensorFlow tools such as Fairness Indicators can be used to detect and mitigate bias, and will then transition to a specific case-study regarding privacy that will walk participants through a couple of infrastructure pieces that can help train a model in a privacy preserving manner.

Introducing a framework to think about ML, fairness and privacy. This talk will propose a fairness-aware ML workflow, illustrate how TensorFlow tools such as Fairness Indicators can be used to detect and mitigate bias, and will then transition to a specific case-study regarding privacy that will walk participants through a couple of infrastructure pieces that can help train a model in a privacy preserving manner.

tensorflow ai machinelearning

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Distributed TensorFlow model training on Cloud AI Platform

Cruise machine learning platform team worked with Google CMLE team together to enable distributed Tensorflow model training with Horovod in 2019. We will pre...

Multi-Label Image Classification in TensorFlow 2.0

In this TensorFlow 2.0 tutorial, I will describe some concepts and tools that you could find interesting when training multi-label image classifiers in TensorFlow 2.0. Do you want to build amazing things with AI? The newly released TensorFlow 2.0 has made deep learning development much easier by integrating more high level APIs. Learn what it takes to predict the genre of a movie from its poster.

Tensorflow Tutorial for Beginners - Tensorflow on Neural Networks

In this TensorFlow tutorial for beginners - TensorFlow on Neural Networks, you will learn TensorFlow concepts like what are Tensors, what are the program elements in TensorFlow , what are constants & placeholders in TensorFlow Python, how variable works in placeholder and a demo on MNIST.

Building Better Artificial Intelligence (AI) Apps with TensorFlow Hub

One of the best things about AI is that you have a lot of open-source content, we use them quite frequently. I will show how TensorFlow Hub makes this process a lot easier and allows you to seamlessly use pre-trained convolutions or word embeddings in your application. We will then see how we could perform Transfer Learning with TF Hub Models and also see how this can expand to other use cases.

TensorFlow Enterprise: Productionizing TensorFlow with Google Cloud

The hardest part of ML adoption in enterprise is Productization. This talk shows us how TensorFlow Enterprise solves these problems with Google Cloud for productionizing your TensorFlow code for mission-critical business operation.