With this week's release of TensorFlow 1.0, Google has pushed the frontiers of machine learning further in a number of directions.

A machine learning workflow with TensorFlow Our architecture consists of training and classification data streamed through Kafka and stored in a persistent, queryable database.

Google LLC today launched an enterprise version of TensorFlow, the popular open-source artificial intelligence framework it created to run machine learning, deep learning and other statistical and ...

Google today announced the launch of version 0.8 of TensorFlow, its open source library for doing the hard computation work that makes machine learning possible. Normally, a small point update ...

Conclusion Exploring machine learning with TensorFlow on Ubuntu opens a world of possibilities. Whether you're a beginner or an experienced practitioner, the combination of TensorFlow's powerful ...

TensorFlow 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.

TensorFlow gives public access to the tools used by Google’s machine learning team.

According to the TensorFlow site, Google open sourced the project to help standardize machine learning systems. “Research in this area is global and growing fast, but lacks standard tools ...

TensorFlow Quantum (TFQ) brings Google quantum computing framework Cirq and TensorFlow together to enable the creation of quantum machine learning (ML) models.

At QCon SF, Daniel Situnayake presented "Machine learning on mobile and edge devices with TensorFlow Lite". TensorFlow Lite is a production-ready, cross-platform framework for deploying ML on ...