TensorRT and TensorFlow 1.7 → https://goo.gl/qGCJyW
Android Studio 3.1 → https://goo.gl/cn2UeW
Wear OS by Google → https://goo.gl/k5GaZT
Stackdriver APM and Stackdriver Profiler → https://goo.gl/dsTgLM
Cloud Text-to-Speech → https://goo.gl/MtvKRL
Kubernetes Engine Private Clusters → https://goo.gl/QQCC8m

Today’s TL;DR is led by Google Developer Advocate Timothy Jordan. The TL;DR is where you can stay up to date on all the latest developer news from across our developer teams at Google.

Check out the latest TL;DR episodes → https://goo.gl/cHuQkL
Subscribe to the Google Developers channel → http://goo.gl/mQyv5L

Nikhil Thorat and Daniel Smilkov discuss TensorFlow.js, which is TensorFlow’s new machine learning framework for JavaScript developers. It supports building ML models in JavaScript, and training and deploying them in browser for execution using WebGL. They focus on tensorflow.js-Core which is a rebranding of deeplearn.js, and a new high-level layers API to make it easier to develop ML models in JavaScript. Initial set of converters for converting saved TF models into JS is also being released.

Visit the site → https://js.tensorflow.org/
Check out the blog for an article on Machine Learning in JavaScript → https://medium.com/tensorflow/

TensorFlow Dev Summit 2018 All Sessions playlist → https://goo.gl/Lsaq1R
Subscribe to the TensorFlow channel → https://goo.gl/ht3WGe

For the code snippets and references: https://nikhilsrambles.substack.com/p/how-to-build-an-insanely-good-image-classifier-in-under-10-minutes
Personal: http://nikhilreddy.io
Twitter: http://bignikhilreddy.io

In this interview of AI Adventures, Yufeng interviews Developer Advocate Sara Robinson to talk about a custom object detection iOS app she built to detect Taylor Swift. We’ll cover everything from training a model with transfer learning, to serving the model in the cloud, to making prediction requests to the model from an iOS device (in Swift!).

Associated Medium blog post: https://goo.gl/SKL5Ro

Sara’s original Medium blog post: https://goo.gl/hKvZfV
Code: https://goo.gl/LZXbbb

TensorFlow Object Detection on GitHub: https://goo.gl/QYThDb
Building a pet detector with the Object Detection API: https://goo.gl/cxIquA
Building a raccoon detector with the Object Detection API: https://goo.gl/A8Sykp
Pascal VOC format: https://goo.gl/m2yT6N
Firebase iOS SDK: https://goo.gl/hnbrva
Cloud Functions for Firebase: https://goo.gl/1qBuce

Watch more AI Adventures: https://goo.gl/UC5usG

Subscribe to get all the episodes as they come out: https://goo.gl/S0AS51

In this episode of AI Adventures, Yufeng journeys to Jupyter to bring back some tips and tricks for your data science workflow!

Associated Medium post “Jupyter tips and tricks”: https://goo.gl/Xi3ffq

http://jupyter.org/

Watch more episodes of AI Adventures: https://goo.gl/UC5usG

Subscribe to get all the episodes as they come out: https://goo.gl/S0AS51