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Inside TensorFlow

TensorFlow via YouTube

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Overview

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This course presents technical deep dives into TensorFlow from members of the TensorFlow team. Topics include runtimes, distributed training, input pipelines, debugging, Keras, TensorFlow Lite, quantization, pruning, and MLIR.

Syllabus

Inside TensorFlow: Parameter server training.
Inside TensorFlow: TF NumPy.
Inside TensorFlow: Building ML infra.
Inside TensorFlow: Quantization aware training.
Inside TensorFlow: New TF Lite Converter.
Inside TensorFlow: TF Debugging.
Inside TensorFlow: TF-Agents.
Inside TensorFlow: tf.data + tf.distribute.
Inside TensorFlow: TF Filesystems.
Inside TensorFlow: TF Model Optimization Toolkit (Quantization and Pruning).
Inside TensorFlow: Eager execution runtime.
Inside TensorFlow: Graph rewriting (Macros, not functions).
Inside TensorFlow: Control Flow.
Inside TensorFlow: tf.data - TF Input Pipeline.
Inside TensorFlow: Summaries and TensorBoard.
Inside TensorFlow: Resources and Variants.
Inside TensorFlow: Functions, not sessions.
Inside TensorFlow: tf.distribute.Strategy.
Inside TensorFlow: tf.Keras (Part 1).
Inside TensorFlow: TensorFlow Lite.
Inside TensorFlow: tf.Keras (part 2).
Inside TensorFlow: AutoGraph.
Inside TensorFlow: MLIR for TF developers.

Taught by

TensorFlow

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