Google AI Blog: The What-If Tool: Code-Free Probing of Machine Learning Models
Posted by James Wexler, Software Engineer, Google AI Building effective machine learning (ML) systems means asking a lot of questions. It's not enough to train a model and walk away. Instead, good practitioners act as detectives, probing to understand their model better: How would changes to a datapoint affect my model’s prediction? Does it perform differently for various groups–for example, histo
Using Evolutionary AutoML to Discover Neural Network Architectures
Posted by Esteban Real, Senior Software Engineer, Google Brain Team The brain has evolved over a long time, from very simple worm brains 500 million years ago to a diversity of modern structures today. The human brain, for example, can accomplish a wide variety of activities, many of them effortlessly — telling whether a visual scene contains animals or buildings feels trivial to us, for example.
Google AI Blog: Eager Execution: An imperative, define-by-run interface to TensorFlow
Posted by Asim Shankar and Wolff Dobson, Google Brain Team UPDATE, April 3 2018: Please see the official user guide for more up-to-date code examples than are shown in this post. Today, we introduce eager execution for TensorFlow. Eager execution is an imperative, define-by-run interface where operations are executed immediately as they are called from Python. This makes it easier to get started w
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TFGAN: A Lightweight Library for Generative Adversarial Networks
Announcing YouTube-8M: A Large and Diverse Labeled Video Dataset for Video Under
Introducing the Open Images Dataset
