TensorFlow Weekly Issue 1

TensorFlow Weekly Issue 1 — July 24, 2018

Hi there, these are the top TensorFlow links from my weekly curation. If you're having trouble viewing this email, please read the online version.

TF Jam — Shooting Hoops with Machine Learning — In this article, we’ll dive into using Unity3D and TensorFlow to teach an AI to perform a simple in-game task: shooting balls into a hoop...
Abe Haskins

Tensorflow - Your CPU supports instructions that this binary was not compiled to use — If you've installed TensorFlow from pip, you've probably come across this message: tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA ... Well, I did too and it got me wondering how much of a difference those instructions end up making. People often say GPUs are required for any non-trivial ML work so I wanted to see if that was really true. I decided to delve in and optimize TensorFlow and make it faster on my machine...
Jason Zaman

Move Mirror: An AI Experiment with Pose Estimation in the Browser using TensorFlow.js — Move Mirror — a project that is a testament to the value that experimentation and play can add to serious engineering work...Read on to get an in-depth view into how we made the experiment, what excites us about pose estimation in the browser, and the ideas on the horizon that we’re excited for...
Jane Friedhoff and Irene Alvarado

AutoGraph converts Python into TensorFlow graphs — We’d like to tell you about a new TensorFlow feature called “AutoGraph”. AutoGraph converts Python code, including control flow, print() and other Python-native features, into pure TensorFlow graph code...
Alex Wiltschko, Dan Moldovan, Wolff Dobson

Prepare your dataset for machine learning with JavaScript [Video] — Interested in learning how to use JavaScript in the browser? In the last episode of Coding TensorFlow, we showed you a very basic ML scenario in the browser that predicted future values. Shaping your data and getting it ready for training is an important step in data science. Watch as Laurence shows how you can prepare your own raw data and get it ready for a machine learning model. In the next episode, we’ll train a neural network with this data, and go into designing the network, and doing classification given the trained model...
Laurence Moroney

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Cheers,
Sebastian