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

François Duval

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商品描述

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Are you thinking of learning more about Deep Learning Concepts and Algorithms?

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.

 Why this Book is different?

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

商品描述(中文翻譯)

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您是否考慮學習更多有關深度學習概念和算法的知識?

如果您正在尋找一本幫助您理解深度學習的概念和算法的書籍,那麼這本書非常適合您。

幾個視覺插圖和範例

方程式非常適合深入理解算法的每一個細節。但為了獲得對事物運作的基本概念,本書包含幾個圖表,詳細說明每個神經網絡/深度學習算法。它還包含幾個實用範例的圖表。

這本書有何不同?

這本書將幫助您探索深度學習的本質,並教您為何它如此革命性和迷人。各章將向讀者介紹深度學習算法的概念、技術和應用,並提供實際案例研究和逐步示範的範例供您練習。

本書採取不同的方法,基於提供簡單的範例來說明深度學習算法的運作,並逐步建立這些範例,以涵蓋算法中更複雜的部分。

目標讀者

本書設計針對多種目標讀者。最合適的使用者包括:
- 電腦科學技術和深度學習的新手
- 數據科學和社會科學的專業人士
- 尋求以最簡單易懂的方式向學生解釋內容的教授、講師或導師
- 學生和學者,特別是那些專注於神經網絡和深度學習的人

這本書裡面有什麼?

- 深度學習的先決條件
- 人工神經網絡簡介
- 人工神經網絡的基本概念
- 深度學習的演變和重複方法
- 機器學習與深度學習之間的關係
- 多層感知器 (MLP)
- 卷積神經網絡 (CNN)
- 其他深度學習算法
- 深度學習應用
- 深度學習中一些有用術語的詞彙表
- 有用的參考資料