Difference between revisions of "TensorFlow"
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| − | + | In TensorFlow 2.0, eager execution is enabled by default, with tight [[Keras]] integration. You can easily ingest datasets via tf.data pipelines, and you can monitor your training in [[TensorBoard]] directly from [[Colaboratory]] and [http://jupyter.org/index.html Jupyter] Notebooks. [http://cloud.google.com/blog/products/ai-machine-learning/tensorflow-2-0-and-cloud-ai-make-it-easy-to-train-deploy-and-maintain-scalable-machine-learning-models TensorFlow 2.0 and [[Google]] Cloud AI make it easy to train, deploy, and maintain scalable machine learning models | Paige Bailey and Barrett Williams - Google] | |
Revision as of 12:00, 7 April 2019
Youtube search... ...Google search
- Libraries & Frameworks
- TensorFlow Overview & Tutorials
- TensorFlow.js ... Browser and Node Server
- TensorFlow Serving .. Cloud, On-prem
- TensorFlow Lite ... Android, iOS, Raspberry Pi
- TensorBoard
- TensorFlow Playground
- We’re making tools and resources available so that anyone can use technology to solve problems | Google AI
In TensorFlow 2.0, eager execution is enabled by default, with tight Keras integration. You can easily ingest datasets via tf.data pipelines, and you can monitor your training in TensorBoard directly from Colaboratory and Jupyter Notebooks. TensorFlow 2.0 and Google Cloud AI make it easy to train, deploy, and maintain scalable machine learning models | Paige Bailey and Barrett Williams - Google
