TensorFlow underlies many Google services. The TensorFlow 2.0 website describes the project as an “end-to-end open source machine learning platform.” ...

TensorFlow 2.0 fires up AI models much faster than previous versions, which lets engineers try out different model variations with shorter delays between test runs.

At the 2019 TensorFlow Dev Summit today, Google announced a number of updates for its open-source machine learning library aimed at research and production. The TensorFlow 2.0 alpha provides a ...

TensorFlow 2.0 will also feature eager execution by default -- this means ops will run immediately upon calling them. The new version also features automatic optimization of eager code with tf ...

Google announced TensorFlow 2.0 is now available for public use. The alpha version of the deep learning library made its debut this spring.

This is new: TensorFlow 2.18 integrates the current version 2.0 of NumPy and, with Hermetic CUDA, will no longer require local CUDA libraries during the build.

Since then, over 400,000 students have enrolled in the course and joined the AI revolution. We’re excited to release an all-new version of this free course featuring the just-announced alpha release ...

Apple released a forked version of Google's TensorFlow framework that's optimized for MacBooks running macOS Big Sur.

The TensorFlow project announced the release of version 2.3.0, featuring new mechanisms for reducing input pipeline bottlenecks, Keras layers for pre-processing, and memory profiling.

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.