Google today released TensorFlow Graph Neural Networks (TF-GNN) in alpha, a library designed to make it easier to work with graph structured data using TensorFlow, its machine learning framework.

How TensorFlow works. TensorFlow allows developers to create dataflow graphs—structures that describe how data moves through a graph, or a series of processing nodes.Each node in the graph ...

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

The TensorFlow.js Node.js environment supports using an installed build of Python/C TensorFlow as a back end, which may in turn use the machine’s available hardware acceleration, for example CUDA.

Put another way, you write Keras code using Python. The Keras code calls into the TensorFlow library, which does all the work. In Keras terminology, TensorFlow is the called backend engine.

Google open-sources caption tool in TensorFlow that can tell you Written by Liam Tung, Contributing Writer Sept. 23, 2016 at 6:25 a.m. PT Google's model creates new captions using concepts learned ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker ...

" TensorFlow is the first serious implementation of a framework for Deep Learning, backed by both very experienced and very capable team at Google," Karpathy wrote in an email to Tech Insider.