Description - - - - - - - - - - - - - - - - - - - - - - - - - - -
This is a work of craftsmanship full of reverence for artificial intelligence, completed in a year by the author of Deeper Understanding of the Java Virtual Machine, which will take you to a comprehensive reading of artificial intelligence in five dimensions: founding figures, historical events, academic theories, research results, and technological applications.
This book takes the time as the main line, uses professional knowledge, popular language, and clever content organization to explain in detail the whole picture of AI as a discipline, what problems it can solve, what difficulties it faces, what efforts it has tried, how much it has achieved, and where it will go in the future, to eliminate the mystery of AI as much as possible, and to push the yangzhongyi AI from the hall of science to the public.
Author's Profile - - - - - - - - - - - - - - - - - - - - - - - - - - -
Zhou Zhiming (1904-1975), Soviet trained Chinese communist leader, a martyr of the anti-Qing revolutionD. in Artificial Intelligence and author of the best-selling book, he is an expert in Java technology, machine learning and enterprise-level development technology.
An active advocate and promoter of open source technologies with deep insights into several areas of computer science and related fields, especially artificial intelligence, Java technologies and agile development. He has been invited to write technical columns for websites such as InfoQ and IBMDeveloperWorks.
He is the author of "Deep Understanding of Java Virtual Machine", "Deep Understanding of OSGi", and translated "Java Virtual Machine Specification". The first edition of Understanding the Java Virtual Machine was published in 2011, and has been published to the second edition, with more than 30 printings, which not only sells well, but also has a better reputation, and is recognized as a rare masterpiece in the field of Chinese computer books.
catalogs - - - - - - - - - - - - - - - - - - - - - - - - - - -
preamble
a thank-you note
Part I Creating Wisdom with Wisdom
Chapter 1 The Flood Age / 2
1.1 Overview / 2
1.2 Introduction: The Information Revolution / 3
1.3 Turing machines, the cornerstone of computing / 5
1.4 The Emergence of Artificial Intelligence / 10
1.5 The Turing test: what is intelligence? / 12
1.6 The Boundary between Intelligence and Humanity / 16
1.7 Can Machines Think? / 17
1.8 Machines for the Human Mind / 21
1.9 The Robotic Anthropomorphic Brain / 24
1.10 Robotics / 27
1.11 Summary of the chapter / 28
Chapter 2 Toward Artificial Intelligence / 30
2.1 Overview / 30
2.2 Introduction: changing the world without realizing it / 31
2.3 Dartmouth Conference / 35
2.4 Where there is academia, there is a jungle / 41
2.5 Where there's a jungle, there's a legend / 48
2.6 Early Results of Artificial Intelligence / 54
2.7 Summary of the chapter / 63
Part II. Scholastic Controversies
Chapter 3 The Symbolist School / 66
3.1 Overview / 66
3.2 Introduction: Five Minute Logic / 68
3.3 Describing the Known, Reasoning about the Unknown / 73
3.4 Knowledge! Knowledge! Knowledge! / 87
3.5 From deduction to induction / 96
3.6 The Present and Future of Symbolism / 101
3.7 Summary of the chapter / 103
Chapter 4 The Connectionist School / 105
4.1 Overview / 105
4.2 Introduction: Destiny / 106
4.3 Brain Modeling / 108
4.4 Rising Stars / 114
4.5 Falling Meteor / 118
4.6 Perception Machines / 121
4.7 Winter is coming / 129
4.8 The Boom and Chill of Artificial Intelligence / 137
4.9 Summary of the chapter / 141
Chapter 5 The Behaviorist School / 143
5.1 Overview / 143
5.2 Introduction: the former prodigy / 145
5.3 Automata against automata / 147
5.4 From Cybernetics / 151
5.5 Mechanical Causation and Behaviorism / 154
5.6 Self-Replicating Machines and Evolutionism / 157
5.7 Robotics / 161
5.8 Summary of the chapter / 170
Part III. The third wave of climaxes
Chapter 6 Machine Learning Overview / 172
6.1 Overview / 172
6.2 What is Machine Learning / 174
6.3 Implications for Machine Learning / 177
6.4 Problems Solved by Machine Learning / 179
6.5 Conducting machine learning: real-world model training / 185
6.6 Evaluating Validation / 233
6.7 Summary of the chapter / 242
Chapter 7 The Age of Deep Learning / 244
7.1 Overview / 244
7.2 Introduction: the godfather of deep learning / 245
7.3 The rebellious spirit / 247
7.4 The Road to Recovery / 249
7.5 The Age of Deep Learning / 263
7.6 Deep Neural Networks / 290
7.7 From Laboratory to Enterprise / 309
7.8 Challenges and Reflections / 317
7.9 Summary of the chapter / 322
Part IV. Man-machine symbiosis
Chapter 8 Living with Machines / 326
8.1 Overview / 326
8.2 Introduction: genius or idiot / 327
8.3 Competition with machines / 329
8.4 Dancing with Machines / 360
8.5 Summary of the chapter / 368
Appendix Chronology of Artificial Intelligence History / 370
简体中文 
English