July 01, 2020 —
Posted by Ashwin Murthy, Software Engineer, TensorFlow team @ Google
OverviewEfficiency and performance are critical for edge deployments. TensorFlow Lite achieves this by means of fusing and optimizing a series of more granular TensorFlow operations (which themselves are composed of composite operations, like LSTM) into a single executable TensorFlow Lite unit.
Many users have asked us for more g…
June 29, 2020 —
Posted byTulsee Doshi, Andrew Zaldivar
As billions of people around the world continue to use products or services with AI at their core, it becomes more important than ever that AI is deployed responsibly: preserving trust and putting each individual user’s well-being first. It has always been our highest priority to build products that are inclusive, ethical, and accountable to our communities,…
June 26, 2020 — Posted by Khanh LeViet, TensorFlow Developer Advocate
June 24, 2020 — Posted by Shuang Song and David Marn
June 18, 2020 — A guest post by Niranjan Hasabnis, Mohammad Ashraf Bhuiyan, Wei Wang, AG Ramesh at Intel
June 17, 2020 —
Posted by Luiz Gustavo Martins, Beat Gfeller and Christian Frank
Pitch is an attribute of musical tones (along with duration, intensity and timbre) that allows you to describe a note as “high” or “low”. Pitch is quantified by frequency, measured in Hertz (Hz), where one Hz corresponds to one cycle per second. The higher the frequency, the higher the note.
June 09, 2020 —
A guest post by Michael Gielda of Antmicro
Every day more and more software developers are exploring the worlds of machine learning, embedded systems, and the Internet of Things. Perhaps one of the most exciting advances to come out of the most recent innovations in these fields is the incorporation of ML at the edge and into smaller and smaller devices - often referred to as TinyML.
June 08, 2020 —
Guest author Hannes Hapke, Senior Data Scientist, SAP Concur Labs. Edited by Robert Crowe on behalf of the TFX team
Transformer models and the concepts of transfer learning in Natural Language Processing have opened up new opportunities around tasks like sentiment analysis, entity extractions, and question-answer problems.
BERT models allow data scientists to stand on the shoulders of giants. Pr…
May 29, 2020 —
Posted by Soonson Kwon, Biswajeet Mallik, and Siddhant Agarwal, Program Managers
TensorFlow User Groups (or TFUGs, for short) are a community of curious, passionate machine learning developers and researchers around the world. TFUGs play an important role in helping developers share their knowledge and experience in machine learning, and the latest TensorFlow updates. Google and the TensorFlow tea…
May 27, 2020 — By Shan Huang, Creative Technologist, Google Partner Innovation
May 21, 2020 —
A guest article by Mike Walmsley, University of Oxford
The way we do science is changing; there’s exponentially more data every day but around the same number of scientists. The traditional approach of collecting data samples, looking through them, and drawing some conclusions about each one is often inadequate.
May 20, 2020 —
Posted by Jessica Yung and Joan Puigcerver
In this article, we'll walk you through using BigTransfer (BiT), a set of pre-trained image models that can be transferred to obtain excellent performance on new datasets, even with only a few examples per class.
May 18, 2020 —
A guest post by Hugging Face: Pierric Cistac, Software Engineer; Victor Sanh, Scientist; Anthony Moi, Technical Lead.
Hugging Face 🤗 is an AI startup with the goal of contributing to Natural Language Processing (NLP) by developing tools to improve collaboration in the community, and by being an active part of research efforts.
April 29, 2020 —
Posted by Eric Johnson, TFRT Product Manager and Mingsheng Hong, TFRT Tech Lead/Manager
TensorFlow aims to make it easy for you to build and deploy ML models across many different devices. Yet, what it means to “build and deploy ML models” is not static and continues to change with increased investment in the ML ecosystem.
April 21, 2020 —
Posted by Laurence Moroney, AI Advocate
I’m excited to share an important aspect of the TensorFlow community: when educators and domain experts teach and train developers how to use machine learning technology to solve important tasks for a variety of scenarios, including in health care. To this end, deeplearning.ai and Coursera have launched an “AI for Medicine” specialization using TensorFlow.
April 20, 2020 —
Posted by Khanh LeViet, Developer Advocate on behalf of the TensorFlow Lite team
Edge devices, such as smartphones, have become more powerful each year and enable an increasing number of on-device machine learning use cases. TensorFlow Lite is the official framework for running TensorFlow model inference on edge devices. It runs on more than 4 billion active devices globally, on various platforms,…
April 17, 2020 —
Posted by Khanh LeViet and Luiz Gustavo Martins, Developer Advocates
Neural style transfer is an optimization technique used to take two images, a content image (such as a building) and a style image (such as artwork by an iconic painter), and blend them together so the output image looks like the content image “painted” in the style of the reference image. Today, we are excited to share a pre-tra…
April 15, 2020 —
Posted by Anirudh Sriram, Technical Writer, and Gal Oshri, Product Manager
Performance is a key consideration of successful ML research and production solutions. Faster model training leads to faster iterations and reduced overhead. It is sometimes an essential requirement to make a particular ML solution feasible.
April 14, 2020 — Posted by Khanh LeViet, Developer Advocate
April 13, 2020 —
Posted by the TensorFlow Team
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 gre…
