TensorFlow data flow graphs TensorFlow supports machine learning, neural networks, and deep learning in the larger context of data flow graphs.

That library, TensorFlow, was developed by the Google Brain team over the past several years and released to open source in November 2015. TensorFlow does computation using data flow graphs.

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.

There is no real middle ground when it comes to TensorFlow use cases. Most implementations take place either in a single node or at the drastic Google-scale, with few scalability stories in between.

While DeepMind’s original implementation uses an older TensorFlow 1.0 framework, which lacks compatibility with recent libraries, we adapt their architecture to TensorFlow 2, exploring the newly ...

The search function in Google Photos uses TensorFlow. Tim Stenovec/Business Insider Google made waves Monday when it made its new artificial intelligence system TensorFlow open source.

“TensorFlow is a machine learning library that’s used across Google for applying deep learning to a lot of different areas,” says Rajat Mongo, a technical lead on the TensorFlow project, in a YouTube ...

TensorFlow Hub encourages the publication and discovery of self-contained modular pieces of TensorFlow graphs for reuse across similar tasks.

TensorFlow Lite (TFLite) was announced in 2017 and Google is now calling it “LiteRT” to reflect how it supports third-party models. TensorFlow Lite for mobile on-device AI has “grown beyond ...