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Grokking Deep Learning
book

Grokking Deep Learning

by Andrew W. Trask
February 2019
Intermediate to advanced content levelIntermediate to advanced
336 pages
9h 29m
English
Manning Publications
Content preview from Grokking Deep Learning

Chapter 8. Learning signal and ignoring noise: introduction to regularization and batching

In this chapter

  • Overfitting
  • Dropout
  • Batch gradient descent

“With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”

John von Neumann, mathematician, physicist, computer scientist, and polymath

Three-layer network on MNIST

Let’s return to the MNIST dataset and attempt to classify it with- h the new network

In last several chapters, you’ve learned that neural networks model correlation. The hidden layers (the middle one in the three-layer network) can even create intermediate correlation to help solve for a task (seemingly out of midair). How do you know the network is creating good correlation?

When we discussed ...

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Publisher Resources

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