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TensorFlow for Machine Intelligence by Ariel Scarpinelli, Erik Erwitt, Danijar Hafner, Troy Mott, Sam Abrahams

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Chapter 3. TensorFlow Fundamentals

Introduction to Computation Graphs

This section covers the basics of computation graphs without the context of TensorFlow. This includes defining nodes, edges, and dependencies, and we also provide several examples to illustrate key principles. If you are experienced and/or comfortable with computation graphs, you may skip to the next section.

Graph basics

At the core of every TensorFlow program is the computation graph described in code with the TensorFlow API. A computation graph, is a specific type of directed graph that is used for defining, unsurprisingly, computational structure. In TensorFlow it is, in essence, a series of functions chained together, each passing its output to zero, one, or more ...

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