TFX enables ML practitioners to iterate ML reliable workflows faster. This blog post discusses building a Semantic Segmentation pipeline with TFX.

Build your own models that can process video or three-dimensional data (such as MRI scans) in a memory-efficient manner using TensorFlow

Posted by Jeff Dean, Senior Fellow and SVP of Google Research, on behalf of the Google Research community Today we kick off a series of blog posts ...

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

This article has been completely generated using ChatGPT, a powerful model released by OpenAI

MediaPipe is adding new ML solutions for the web. Use MediaPipe Solutions to create custom ML experiences for your web applications.

TensorFlow Decision Forests is production ready! In this post, we are going to show you all the new features that come with it.

To celebrate our last 4.8.2 release, we'd like to reflect on the progress made over these past years and thank the community for their support.

You can help reduce the risk of language deprivation for deaf children by joining our new Isolated Sign Language Recognition competition on Kaggle.

Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.

Throughout the 8 modules in this course…

Now, all models from Google and Deepmind published on TFHub are more easily accessible to the broader ML community on the new Kaggle Models!

Vodafone leverages Google Cloud to deploy AI/ML use cases at scale.

Learn how to use TensorFlow with MATLAB by converting deep learning models or running Python and MATLAB code together.

Whether you’re just getting started in AI/ML, or looking to expand your established experience, these stories are for you. We hope you will tune in!

TensorFlow 2.12 has been released! Highlights of this release include the new Keras model saving and exporting format, and many more exciting updates.

TensorFlow developers can now leverage the optimizations in the AMD ZenDNN library through a newly available TensorFlow-ZenDNN plug-in.

Learn how Adobe uses Web ML, providing end users with lower latency than cloud based solutions; that’s key to a better user experience.

We're excited to announce the launch of CLP – a new technique in the TF Model Remediation Library that lets you build fairer ML systems.

We explain end-to-end how to use the dynamic embeddings in the TensorFlow Recommenders Addons library with the TensorFlow Recommenders library.

The TensorFlow blog contains regular news from the TensorFlow team and the community, with articles on Python, TensorFlow.js, TF Lite, TFX, and more.