Difference between revisions of "TensorFlow"
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* [http://developers.google.com/machine-learning/crash-course/ Machine Learning Crash Course with TensorFlow APIs | Google] | * [http://developers.google.com/machine-learning/crash-course/ Machine Learning Crash Course with TensorFlow APIs | Google] | ||
* [http://www.youtube.com/results?search_query=Martin+Gorner TensorFlow without a PhD | Martin Görner] | * [http://www.youtube.com/results?search_query=Martin+Gorner TensorFlow without a PhD | Martin Görner] | ||
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* [http://www.slideshare.net/matthiasfeys/running-tensorflow-in-production/1 Running Tensorflow in Production | Matthias Feys] | * [http://www.slideshare.net/matthiasfeys/running-tensorflow-in-production/1 Running Tensorflow in Production | Matthias Feys] | ||
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* [http://www.notion.so/Simple-Tensorflow-Cookbook-6f4563d0cd7343cb9d1e60cd1698b54d Simple Tensorflow Cookbook] | * [http://www.notion.so/Simple-Tensorflow-Cookbook-6f4563d0cd7343cb9d1e60cd1698b54d Simple Tensorflow Cookbook] | ||
* [http://github.com/machinelearningmindset/TensorFlow-Course TensorFlow-Course | GitHub] | * [http://github.com/machinelearningmindset/TensorFlow-Course TensorFlow-Course | GitHub] | ||
| − | + | * [[Git - GitHub and GitLab]] | |
* Related... | * Related... | ||
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==== TensorFlow 2.0 ==== | ==== 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 [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] | 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 [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] | ||
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| + | * [http://medium.com/tensorflow/whats-coming-in-tensorflow-2-0-d3663832e9b8 What’s coming in TensorFlow 2.0 | TensorFlow Team - Medium] | ||
| + | * [http://jaxenter.com/ml-tensorflow-2-0-154466.html What’s in store for ML developers in TensorFlow 2.0? | Jane Elizabeth] | ||
<youtube>b5Rs1ToD9aI</youtube> | <youtube>b5Rs1ToD9aI</youtube> | ||
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<youtube>skf35x1lNV4</youtube> | <youtube>skf35x1lNV4</youtube> | ||
<youtube>Q6ERFwQNkzo</youtube> | <youtube>Q6ERFwQNkzo</youtube> | ||
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==== Eager Execution (Default in 2.0) ==== | ==== Eager Execution (Default in 2.0) ==== | ||
Revision as of 20:14, 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
- Keras
- TensorFlow Workshops click on links to run in Colaboratory
- 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
- 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)
