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 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 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.

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.

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 ...

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.

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.

Our data science doctor provides a hands-on neural networking tutorial to explain how to get started with the popular Keras library, a high-level wrapper over TensorFlow.