• Title: Grokking Deep Learning
• Author: Andrew Trask
• Length: 325 pages
• Edition: 1
• Language: English
• Publisher: Manning Publications
• Publication Date: 2019-01-25
• ISBN-10: 1617293709
• ISBN-13: 9781617293702
  

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Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the "brain" behind the world's smartest Artificial Intelligence systems out there.

Grokking Deep Learning is the perfect place to begin the deep learning journey. Rather than just learning the "black box" API of some library or framework, readers will actually understand how to build these algorithms completely from scratch.

Want to dig even deeper into Deep Learning? Be sure to check out our video course Grokking Deep Learning in Motion, available exclusively at Manning.com (https://www.manning.com/livevideo/​grokking-deep-learning-in-motion)!

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Table of contents

Chapter 1   

      Introducing Deep Learning: Why You Should Learn It
Chapter 2   

      Fundamental Concepts: How Do Machines Learn
Chapter 3   

      Introduction To Neural Prediction: Forward Propagation
Chapter 4   

      Introduction To Neural Learning: Gradient Descent
Chapter 5   

      Learning Multiple Weights At A Time: Generalizing Gradient Descent
Chapter 6   

      Building Your First Deep Neural Network: Introduction To Backpropagation
Chapter 7   

      How To Picture Neural Networks: In Your Head And On Paper
Chapter 8   

      Learning Signal And Ignoring Noise: Introduction To Regularization And Batching
Chapter 9   

      Modeling Probabilities And Nonlinearities: Activation Functions
Chapter 10  

      Neural Learning About Edges And Corners: Intro To Convolutional Neural Networks
Chapter 11  

      Neural Networks That Understand Language: King
Chapter 12  

      Neural Networks That Write Like Shakespeare: Recurrent Layers For Variable-Length Data
Chapter 13  

      Introducing Automatic Optimization: Let

Chapter 14  

      Learning To Write Like Shakespeare: Long Short-Term Memory
Chapter 15  

      Deep Learning On Unseen Data: Introducing Federated Learning
Chapter 16  

      Where To Go From Here: A Brief Guide