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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
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
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Toc

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

Questions

Let's examine our knowledge of autoencoders by answering the following questions:

  1. What are autoencoders?
  2. What is the objective function of autoencoders?
  3. How do convolutional autoencoders differ from vanilla autoencoders?
  4. What are denoising autoencoders?
  5. How is the average activation of the neuron computed?
  6. Define the loss function of contractive autoencoders.
  7. What are the Frobenius norm and Jacobian matrix?
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Authors (1)

Profile icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more
See other products by Sudharsan Ravichandiran

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