Difference between revisions of "TensorFlow"

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Revision as of 07:44, 9 October 2023

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TensorFlow 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

GPU

tf.function

Eager Execution (Default in 2.0) =

tf.data - TF Input Pipeline

tf.distribute

mesh-TensorFlow

TensorFlow Probability

Reinforcement Learning with TF-Agents

Examples


Tensorflow for Practice Specialization