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Introduction on Keynote Tensorflow Dev Summit 2018
Main Features
History
Video Highlights & Reports
Future Outlook

Introduction on Keynote Tensorflow Dev Summit 2018

Brennan Saeta walks through how to optimize training speed of your models on modern accelerators (GPUs and TPUs). We have seen tremendous advances in many different areas of machine learning. The use of Edd Wilder-James announces a new set of mailing lists to help communication and coordination, the expansion of the SIG ... In 2016, Coca-Cola updated its core loyalty marketing program to a mobile-first web platform. The program requires consumers to ... Alex Passos discusses Eager Execution, which provides a simpler, more intuitive interface to Ian Langmore reconstructs plasma temperature, density, and B-field from measurements in partnership with tae.com. This is a ...

Magenta explores the role of ML in the process of creating art and music. This involves developing new deep learning and ... Getting the most out of Machine Learning models requires careful tuning of many knobs. In this short talk, Vijay Vasudevan ... 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 Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ... Alex Irpan discusses real-world robot learning. In the past, research has shown that with enough real world robot data, we can ...