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tensorflow
 
TensorFlow Wikipedia.
26 In January 2019, TensorFlow team released a developer preview of the mobile GPU inference engine with OpenGL ES 3.1 Compute Shaders on Android devices and Metal Compute Shaders on iOS devices. 27 In May 2019, Google announced that their TensorFlow Lite Micro also known as TensorFlow Lite for Microcontrollers and ARM's' uTensor would be merging.
TensorFlow for R.
In the tutorials section you will find documentation for solving common Machine Learning problems using TensorFlow. The guide section contains documents with in depth explanations of how TensorFlow works. TensorFlow is an open source software library for numerical computation using data flow graphs.
TensorFlow.
Train a neural network to classify images of clothing, like sneakers and shirts, in this fast-paced overview of a complete TensorFlow program. Start with building and training a retrieval model to predict a set of movies that a user is likely to watch, and then use a ranking model to create recommendations.
TensorFlow Medium.
TensorFlow 2.0 is now available! Earlier this year, we announced TensorFlow 2.0 in alpha at the TensorFlow Dev Summit. Today, were delighted to announce that the final. Sep 30, 2019. Introducing Neural Structured Learning in TensorFlow. Introducing Neural Structured Learning in TensorFlow.
tensorflow GitHub.
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and training your Keras and TensorFlow code in a local environment to distributed training in the cloud. cloud tensorflow keras gcp. Python Apache-2.0 19 122 22 5 Updated Aug 5, 2020.
Introduction to TensorFlow Machine Learning Crash Course.
TensorFlow is a rich system for managing all aspects of a machine learning system; however, this class focuses on using a particular TensorFlow API to develop and train machine learning models. See the TensorFlow documentation for complete details on the broader TensorFlow system.
GitHub tensorflow/tensorflow: An Open Source Machine Learning Framework for Everyone.
We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow. The TensorFlow project strives to abide by generally accepted best practices in open-source software development.:

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