TensorFlow is built around a concept of Static Computational Graph (SCG). That means, first you define everything that is going to happen inside your framework, then you run it.

Software 2.0, Compute 2.0, and Computational Graphs Graphcore talks about Compute 2.0, others talk about Software 2.0 . These two are strongly related as the new paradigm for application development.

On the more technical side, TensorFlow’s eager execution feature will exit beta. It’s designed to simplify the process of setting up and executing a computational graph, which TensorFlow ...

A consequence of this decision is that Keras has its own graph datastructure for handling computational graphs, rather than relying on the native graph datastructure from TensorFlow or Theano.

TensorFlow data flow graphs. TensorFlow supports machine learning, ... In TensorFlow (named for the flow of tensors along the edges) you can assign each node to a computational device, ...

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.

This is Google’s animated illustration of how tensors flow from node to node through the edges of a data flow graph. TensorFlow currently runs on Ubuntu Linux, MacOS, Android, iOS, and Raspberry ...

The new program offers practitioner level skills in new-generation Machine Learning through hands-on projects. Silicon-valley based global lifelong learning platform Udacity recently announced the ...

Minor-Free Graph: A graph that does not contain a specified smaller graph (minor) as a subgraph, which is critical for certifying graph classes and in achieving computational optimisations.