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Distributed TensorFlow (TensorFlow Dev Summit 2018)
Training Performance: A user’s guide to converge faster (TensorFlow Dev Summit 2018)
tf.data: Fast, flexible, and easy-to-use input pipelines (TensorFlow Dev Summit 2018)
Keynote (TensorFlow Dev Summit 2018)
TensorFlow Hub (TensorFlow Dev Summit 2018)
Inside TensorFlow: Eager execution runtime
Swift for TensorFlow - TFiwS (TensorFlow Dev Summit 2018)
Searching Over Ideas (TensorFlow Dev Summit 2018)
TensorFlow Dev Summit 2018 Highlights
TensorFlow Dev Summit 2018 - Livestream
TensorFlow Lite (TensorFlow Dev Summit 2018)
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Last Updated: September 26, 2026
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Summary
Meet Alex Passos, Software Engineer on the Download 1M+ code from codegive.com/767fa1f Clemens Mewald and Raz Mathias present TFX, which is an end-to-end ML platform built around Igor Saprykin offers a way to train models on one machine and multiple GPUs and introduces an API that is foundational for ... Brennan Saeta walks through how to optimize training speed of your models on modern accelerators (GPUs and TPUs). Derek Murray discusses tf.data, the recommended API for building input pipelines in Andrew Gasparovic and Jeremiah Harmsen dicuss TF Hub, a new library built to foster the publication, discovery, and ... Chris Lattner and Richard Wei unveil Swift for Getting the most out of Machine Learning models requires careful tuning of many knobs. In this short talk, Vijay Vasudevan ... We have seen tremendous advances in many different areas of machine learning. The use of Sarah Sirajuddin and Andrew Selle discuss
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