Deep Learning
eBook - ePub

Deep Learning

A Comprehensive Guide

  1. 290 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Deep Learning

A Comprehensive Guide

About this book

Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively.

Key Features

  • Includes the smooth transition from ML concepts to DL concepts
  • Line-by-line explanations have been provided for all the coding-based examples
  • Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away
  • Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets
  • Every chapter starts with the objective and ends with a set of quiz questions to test the reader's understanding
  • Includes references to the related YouTube videos that provide additional guidance

AI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.

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Yes, you can access Deep Learning by Shriram K Vasudevan,Sini Raj Pulari,Subashri Vasudevan in PDF and/or ePUB format, as well as other popular books in Computer Science & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. The Authors
  8. Chapter 1 Introduction to Deep Learning
  9. Chapter 2 The Tools and the Prerequisites
  10. Chapter 3 Machine Learning: The Fundamentals
  11. Chapter 4 The Deep Learning Framework
  12. Chapter 5 CNN – Convolutional Neural Networks: A Complete Understanding
  13. Chapter 6 CNN Architectures: An Evolution
  14. Chapter 7 Recurrent Neural Networks
  15. Chapter 8 Autoencoders
  16. Chapter 9 Generative Models
  17. Chapter 10 Transfer Learning
  18. Chapter 11 Intel OpenVino: A Must-Know Deep Learning Toolkit
  19. Chapter 12 Interview Questions and Answers
  20. Index