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Celebrating TensorFlow’s First Year

Wednesday, November 9, 2016

Posted by Zak Stone, Product Manager for TensorFlow, on behalf of the TensorFlow team
(Cross-posted on the Google Open Source Blog & Google Developers Blog)Google Brain Teamopen-sourced TensorFlowmake technology work better for everyoneTensorFlowthe most popular

numerous performance improvementsadded support for distributed trainingbrought TensorFlow to iOSRaspberry Pibig data infrastructureGoRustHaskellreleased state-of-the-art image classification modelsGitHubStackOverflowTensorFlow mailing listmajor improvements to Google TranslateTensor Processing UnitsProject Magentaproduce melodiesautomatically interpolate between artistic stylesDeepMinddecided to use TensorFlowfascinating generative models

Australian marine biologists are using TensorFlow to find sea cows in tens of thousands of hi-res photos to better understand their populations, which are under threat of extinction.

An enterprising Japanese cucumber farmer trained a model with TensorFlow to sort cucumbers by size, shape, and other characteristics.

Radiologists have adapted TensorFlow to identify signs of Parkinson’s disease in medical scans.

Data scientists in the Bay Area have rigged up TensorFlow and the Raspberry Pi to keep track of the Caltrain.

The TensorFlow Serving project simplifies the process of serving TensorFlow models in production.

TensorFlow “Wide and Deep” models combine the strengths of traditional linear models and modern deep neural networks.

For those who are interested in working with TensorFlow in the cloud, Google Cloud Platform recently launched Cloud Machine Learning, which offers TensorFlow as a managed service.

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