Covers: theory of Computational Graph
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Questions this item addresses:
  • Explains what is a computational graph
How to use this item?

Read the section 6.5.1

Author(s) / creator(s) / reference(s)
Deep learning book
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Recipe
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Computational Graphs

Collaborators
Total time needed: ~2 hours
Objectives
This lst helps you understand about computational graphs and how they are used in Deep Learning
Potential Use Cases
Mathematical foundations behind Deep Learning
Who is this for ?
INTERMEDIATEPeople interested in knowing how Deep Learning model training works.
Click on each of the following annotated items to see details.
BOOK_CHAPTER 1. Intuitive understanding of Computational Graph
  • Explains what is a computational graph
10 minutes
ARTICLE 2. Computational Graph in Deep learning
  • Example of using Computational Graph for BackPropagation
15 minutes
BOOK_CHAPTER 3. Subroutines for nodes in a computational graph
  • What are the subroutines to be followed in a computational graph?
20 minutes
ARTICLE 4. Symbol to symbol and Symbol to number derivatives
  • Intuitive understanding of Symbol to symbol and Symbol to number derivatives
10 minutes
OTHER 5. [Long read] Detailed explanation of Computation Graph and how to apply BackPropagation over it.
  • What is computation graph?
  • How to apply backprop?
60 minutes

Concepts Covered

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