January 23, 2020 — Posted by the TensorFlow team

January 22, 2020 — Posted by Ruoyu Liu and Robert Crowe on behalf of the TFX team

TensorFlow Extended (TFX) is a platform for creating production-ready machine learning (ML) pipelines. TFX was created by Google and provides the backbone of Google’s ML services and applications, and now Google has open sourced TFX for anyone who wants to create production ML pipelines.

January 16, 2020 — A guest post by Tencent QQ Music Audio Engineering Team

January 15, 2020 — A guest post by Michael Wang and Noemie Guerin from Companion

January 14, 2020 — Posted by Kangyi Zhang, Sandeep Gupta, and Brijesh Krishnaswami

January 07, 2020 — A guest post by Liang Bao, Chengqi Lv, from Ecovacs Robotics AI Department.
Translated by Ziqian Xu, from Ecovacs Robotics Technology Development Department.

December 23, 2019 — Posted by the TensorFlow Team

2019 was an exciting year for TensorFlow. From releasing TensorFlow 2.0 and several product updates to hosting a global roadshow in 11 different countries and the first ever TensorFlow World, this year highlighted how TensorFlow is helping to empower developers, researchers, and enterprises around the world to solve challenging, real-world problems with ML. With Tens…

December 19, 2019 — By Jordan Grimstad
It’s been a year and a half since we introduced TensorFlow Hub, an open-source repository of ready to use pre-trained models published by Google and DeepMind. Since then, we’ve published hundreds of models -- some that are general-purpose and fine-tunable to specific tasks, others which are more specialized -- to help you get faster, smarter ML applications even with little dat…

December 16, 2019 — Posted by Karim Nosseir and Sachin Joglekar, Software Engineers

Digital Signal Processors (DSPs), such as Hexagon DSPs, are microprocessors present on most modern phones alongside other compute units such as the CPU and GPU. Developed with the primary goal of improving communication and multimedia processing, these chips can dramatically speed up model inference on mobile / edge devices. DSPs are …

December 12, 2019 — Posted by Pavel Senchanka, Software Engineering Intern at Google

TensorFlow Lite is an industry-leading solution for on-device inference with machine learning models. While a complete training solution for TensorFlow Lite is still in progress, we're delighted to share with you a new on-device transfer learning example. This illustrates a way of personalizing your machine learning models on-d…

December 11, 2019 — Posted by Catherina Xu and Tulsee Doshi, Product Managers, Google Research

While industry and academia continue to explore the benefits of using machine learning (ML) to make better products and tackle important problems, algorithms and the datasets on which they are trained also have the ability to reflect or reinforce unfair biases. For example, consistently flagging non-toxic text comments fro…

December 10, 2019 — A guest post by Longfei Xiong, Cheng Du, Ronghua Chen, Hui Zheng and Xuhua Hu from WPS AI Engineering Team
Machine learning use cases at KingSoftWPS Office from Kingsoft is a productivity tool that serves 150M+ users globally. We strive to provide the best tools and features to our users so that they can get their document processing done efficiently. Using TensorFlow, we can help our users to pro…

December 06, 2019 — When the TensorFlow YouTube channel launched in 2018, we had a vision to inform and inspire developers around the world about what was possible with Machine Learning. With series like Coding TensorFlow showing how you can use it, and Made with TensorFlow showing inspirational stories about what people have done with TensorFlow and much more, the channel has grown greatly. But we learned an import…

December 02, 2019 — Posted by Gal Oshri, Product Manager

TensorBoard, TensorFlow’s visualization toolkit, is often used by researchers and engineers to visualize and understand their ML experiments. It enables tracking experiment metrics, visualizing models, profiling ML programs, visualizing hyperparameter tuning experiments, and much more.

November 26, 2019 — A guest post by Anne Dattilo, a PhD student in Astronomy and Astrophysics at the University of California Santa Cruz.
IntroductionWhat is an exoplanet? How do we find them? Most importantly, why do we want to find them? Exoplanets are planets outside of our Solar System - they orbit any star other than our Sun. We can find these exoplanets via a few methods: radial velocity, transits, direct imagi…

November 25, 2019 — Posted by Charles Chen, Joe Lee, and Kenny Song on behalf of the TFX team

November 22, 2019 — A guest post by Victor Dibia

As a researcher with interests in human computer interaction and applied machine learning, some of my work has focused on creating tools that leverage the human body as an input device for creating engaging user experiences.

November 19, 2019 — When the TensorFlow YouTube channel launched in 2018, we had a vision to inform and inspire developers around the world about what was possible with Machine Learning. With series like Coding TensorFlow showing how you can use it, and Made with TensorFlow showing inspirational stories about what people have done with TensorFlow and much more, the channel has grown greatly. But we learned an import…

November 18, 2019 — Update(November 18th,  2019)

BodyPix 2.0 has been released, with multi-person support and improved accuracy (based on ResNet50), a new API, weight quantization, and support for different image sizes. Try the new demo live in your browser, and visit our GitHub repo.

November 15, 2019 — A guest post by Guillaume Klein, research engineer at SYSTRAN.

OpenNMT-tf is a neural machine translation toolkit for TensorFlow released in 2017. At that time, the project used many features and capabilities offered by TensorFlow: training and evaluation with tf.estimator, variable scopes, graph collections, tf.contrib, etc. We enjoyed using these features together for more than 2 years.

We spent…