Deep Learning: Deep Learning for Beginners: Concepts and Algorithms (Data Sciences Book 1) by François Duval

Deep Learning: Deep Learning for Beginners: Concepts and Algorithms (Data Sciences Book 1)

Book Title: Deep Learning: Deep Learning for Beginners: Concepts and Algorithms (Data Sciences Book 1)

Publisher: CreateSpace Publishing

Author: François Duval


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François Duval with Deep Learning: Deep Learning for Beginners: Concepts and Algorithms (Data Sciences Book 1)

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Are you thinking of learning more about Deep Learning?


If you are looking for a book to help you understand concepts and algorithms of deep learning, then this is a good book for you. 

 Several Visual Illustrations and Examples


Equations are great for really understanding every last detail of an algorithm.  But to get a basic idea of how things work, this book contains several graphs which detail each neural networks/deep learning algorithms. It is contains also several graphs for the practical examples.

 This Is a Practical Guide Book


This book will help you explore exactly what deep learning is and will also teach you about why it is so revolutionary and fascinating. The chapters will introduce the reader to the concepts, techniques, and applications of deep learning algorithms with the practical case studies and walk-through examples on which to practice.

This book takes a different approach that is based on providing simple examples of how deep learning algorithms work, and building on those examples step by step to encompass the more complicated parts of the algorithms. 



Target Users


The book designed for a variety of target audiences. The most suitable users would include: 
  • Newbies in computer science techniques and deep learning
  • Professionals in data science and social sciences
  • Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way 
  • Students and academicians, especially those focusing on neural networks and deep learning


What’s inside this book?



  • Pre-requisite for Deep Learning
  • Introduction to Artificial Neural Networks
  • The Basics of Artificial Neural Networks
  • Deep Learning Evolution and Recurring Methods
  • Relationship between machine learning and deep learning
  • Multilayer Perceptron (MLP)
  • Convolutional Neural Networks (CNN)
  • Other Deep Learning Algorithms
  • Deep Learning Applications
  • Glossary of Some Useful Terms in Deep Learning
  • Useful References