TensorFlow, Google’s open source deep learning framework, has announced a release candidate for a full-blown version 1.0.
Version 1.0 not only brings improvements to the framework’s gallery of machine learning functions, but also eases TensorFlow development to Python and Java users and improves debugging.
A new compiler that optimizes TensorFlow computations opens the door to a new class of machine learning apps that can run on smartphone-grade hardware.[ Docker, Amazon, TensorFlow, Windows 10, and more: See InfoWorld’s 2017 Technology of the Year Award winners. | Cut to the key news in technology trends and IT breakthroughs with the InfoWorld Daily newsletter, our summary of the top tech happenings. ]
Another slice of Py, Java on the side
Since Python’s one of the biggest platforms for building and working with machine learning applications, it’s only fitting that TensorFlow 1.0 focuses on improving Python interactions.
The TensorFlow Python API has been upgraded so that the syntax and metaphors TensorFlow uses are a better match for Python’s own, offering better consistency between the two.To read this article in full or to leave a comment, please click here