Train in TensorFlow and deploy in Core ML with Tools 0.7

Apple has updated Core ML Tools to version 0.7. Included is a new TensorFlow converter that lets developers train machine learning models in Google's TensorFlow and deploy them with Apple's Core ML

From the Google Developers Blog:

Today, in collaboration with Apple, we are happy to announce support for Core ML! With this announcement, iOS developers can leverage the strengths of Core ML for deploying TensorFlow models. In addition, TensorFlow Lite will continue to support cross-platform deployment, including iOS, through the TensorFlow Lite format (.tflite) as described in the original announcement.

Core ML Tools 0.7 also includes support for custom layers, so you can quickly create, test, and deploy new layers using Core ML on iOS 11.2 or later.

Floating Point 16 (FP16) is included for neural networks as well, which should reduce model sizes by half.

You can find more, and download now, on GitHub and Pyp

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Rene Ritchie is one of the most respected Apple analysts in the business, reaching a combined audience of over 40 million readers a month. His YouTube channel, Vector, has over 90 thousand subscribers and 14 million views and his podcasts, including Debug, have been downloaded over 20 million times. He also regularly co-hosts MacBreak Weekly for the TWiT network and co-hosted CES Live! and Talk Mobile. Based in Montreal, Rene is a former director of product marketing, web developer, and graphic designer. He's authored several books and appeared on numerous television and radio segments to discuss Apple and the technology industry. When not working, he likes to cook, grapple, and spend time with his friends and family.