Difference between revisions of "TensorFlow"
| Line 14: | Line 14: | ||
* [[TensorFlow Lite]] ... Android, iOS, Raspberry Pi | * [[TensorFlow Lite]] ... Android, iOS, Raspberry Pi | ||
* [[TensorBoard]] | * [[TensorBoard]] | ||
| + | * [http://www.tensorflow.org/tfx TensorFlow Extended: an end-to-end platform for deploying production-ready ML pipelines.] | ||
* [http://playground.tensorflow.org TensorFlow Playground] | * [http://playground.tensorflow.org TensorFlow Playground] | ||
* [http://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI] | * [http://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI] | ||
Revision as of 13:47, 19 May 2019
Youtube search... ...Google search
- Libraries & Frameworks
- TensorFlow 2.0 Alpha
- TensorFlow.js ... Browser and Node Server
- TensorFlow Serving .. Cloud, On-prem
- TensorFlow Lite ... Android, iOS, Raspberry Pi
- TensorBoard
- TensorFlow Extended: an end-to-end platform for deploying production-ready ML pipelines.
- TensorFlow Playground
- We’re making tools and resources available so that anyone can use technology to solve problems | Google AI
- Keras
- TensorFlow Workshops click on links to run in Colaboratory (Colab)
- Machine Learning Crash Course with TensorFlow APIs | Google
- TensorFlow without a PhD | Martin Görner
- Running Tensorflow in Production | Matthias Feys
- Simple Tensorflow Cookbook
- TensorFlow-Course | GitHub
- Git - GitHub and GitLab
- The API...
- tf.estimator: available alongside the newer Keras high-level API.
- tf.function: a wrapper to use when writing certain functions in Python]
- Coding TensorFlow <--- video series
TensorFlow 2.0
TensorFlow 2.0 focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform, 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
- What’s coming in TensorFlow 2.0 | TensorFlow Team - Medium
- What’s in store for ML developers in TensorFlow 2.0? | Jane Elizabeth
TensorFlow 1.0
Eager Execution (Default in 2.0)
