July 2019
Intermediate to advanced
512 pages
19h 39m
English
Content preview from Hands-On Deep Learning Algorithms with Python
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Chapter 2 - Getting to Know TensorFlow
- Every computation in TensorFlow is represented by a computational graph. It consists of several nodes and edges, where nodes are the mathematical operations, such as addition, multiplication, and so on, and edges are the tensors. A computational graph is very efficient in optimizing resources and it also promotes distributed computing.
- A computational graph with the operations on the node and tensors to its edges will only be created, and in order to execute the graph, we use a TensorFlow session.
- A TensorFlow session can be created using tf.Session(), and it will allocate the memory for storing the current value of the variable.
- Variables are the containers used to store values. Variables will be ...
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