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Hands-On Deep Learning Algorithms with Python

You're reading from   Hands-On Deep Learning Algorithms with Python Master deep learning algorithms with extensive math by implementing them using TensorFlow

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Product type Paperback
Published in Jul 2019
Publisher Packt
ISBN-13 9781789344158
Length 512 pages
Edition 1st Edition
Languages
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Getting Started with Deep Learning FREE CHAPTER
2. Introduction to Deep Learning 3. Getting to Know TensorFlow 4. Section 2: Fundamental Deep Learning Algorithms
5. Gradient Descent and Its Variants 6. Generating Song Lyrics Using RNN 7. Improvements to the RNN 8. Demystifying Convolutional Networks 9. Learning Text Representations 10. Section 3: Advanced Deep Learning Algorithms
11. Generating Images Using GANs 12. Learning More about GANs 13. Reconstructing Inputs Using Autoencoders 14. Exploring Few-Shot Learning Algorithms 15. Assessments 16. Other Books You May Enjoy

Introduction to Deep Learning

Deep learning is a subset of machine learning inspired by the neural networks in the human brain. It has been around for a decade, but the reason it is so popular right now is due to the computational advancements and availability of the huge volume of data. With a huge volume of data, deep learning algorithms outperform classic machine learning. It has already been transfiguring and extensively used in several interdisciplinary scientific fields such as computer vision, natural language processing (NLP), speech recognition, and many others.

In this chapter, we will learn about the following topics:

  • Fundamental concepts of deep learning
  • Biological and artificial neurons
  • Artificial neural network and its layers
  • Activation functions
  • Forward and backward propagation in ANN
  • Gradient checking algorithm
  • Building an artificial neural network from scratch...
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