Artificial Intelligence For Humans Volume 1 Fundamental Algorithms English Edition Book PDF, EPUB Download & Read Online Free

Artificial Intelligence for Humans, Volume 3
Author: Jeff Heaton
Publisher: Createspace Independent Publishing Platform
ISBN: 1505714346
Pages: 374
Year: 2015-10-28
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Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We examine current neural network technologies, including ReLU activation, stochastic gradient descent, cross-entropy, regularization, dropout, and visualization.
Artificial Intelligence for Humans, Volume 2
Author: Jeff Heaton
Publisher: CreateSpace
ISBN: 1499720572
Pages: 242
Year: 2014-05-28
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Nature can be a great source of inspiration for artificial intelligence algorithms because its technology is considerably more advanced than our own. Among its wonders are strong AI, nanotechnology, and advanced robotics. Nature can therefore serve as a guide for real-life problem solving. In this book, you will encounter algorithms influenced by ants, bees, genomes, birds, and cells that provide practical methods for many types of AI situations. Although nature is the muse behind the methods, we are not duplicating its exact processes. The complex behaviors in nature merely provide inspiration in our quest to gain new insights about data. Artificial Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. No knowledge of biology is needed to read this book. With a forward by Dave Snell.
Artificial Intelligence for Humans
Author: Jeff Heaton
Publisher:
ISBN:
Pages:
Year: 2013
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Artificial Intelligence for Humans, Volume 1
Author: Jeff Heaton
Publisher: CreateSpace
ISBN: 1493682229
Pages: 222
Year: 2013-11-26
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A great building requires a strong foundation. This book teaches basic Artificial Intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, Nelder Mead, and linear regression. These are not just foundational algorithms for the rest of the series, but are very useful in their own right. The book explains all algorithms using actual numeric calculations that you can perform yourself.Artificial Intelligence for Humans is a book series meant to teach AI to those without an extensive mathematical background. The reader needs only a knowledge of basic college algebra or computer programming—anything more complicated than that is thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, R, Python and C. Other languages planned.
Paradigms of Artificial Intelligence Programming
Author: Peter Norvig
Publisher: Morgan Kaufmann
ISBN: 0080571158
Pages: 946
Year: 2014-06-28
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Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.
Artificial Intelligence: The Basics
Author: Kevin Warwick, Professor of Cybernetics Kevin Warwick
Publisher: Routledge
ISBN: 1136629831
Pages: 192
Year: 2013-03-01
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'if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory input in machine systems the nature of consciousness the controversial culturing of human neurons. Exploring issues at the heart of the subject, this book is suitable for anyone interested in AI, and provides an illuminating and accessible introduction to this fascinating subject.
Introduction to Artificial Intelligence
Author: Philip C. Jackson
Publisher: Courier Corporation
ISBN: 0486152723
Pages: 512
Year: 2013-02-19
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Comprehensive survey of artificial intelligence — the study of how computers can be made to act intelligently. Includes introductory and advanced material. Extensive notes updating the main text. 132 illustrations.
Programming Neural Networks with Encog 3 in Java
Author: Jeff Heaton
Publisher:
ISBN: 1604390212
Pages: 242
Year: 2011
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Beginning where our introductory neural network programing book left off, this book introduces you to Encog. Encog allows you to focus less on the actual implementation of neural networks and focus on how to use them. Encog is an advanced neural network programming framework that allows you to create a variety of neural network architectures using the Java programming language. Neural network architectures such as feedforward/perceptrons, Hopfield, Elman, Jordan, Radial Basis Function, and Self Organizing maps are all demonstrated. This book also shows how to use Encog to train neural networks using a variety of means. Several propagation techniques, such as back propagation, resilient propagation (RPROP) and the Manhattan update rule are discussed. Additionally, training with a genetic algorithm and simulated annealing is discussed as well. You will also see how to enhance training using techniques such as pruning and hybrid training.
Introduction to Neural Networks with Java
Author: Jeff Heaton
Publisher: Heaton Research, Inc.
ISBN: 1604390085
Pages: 440
Year: 2008
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Introduction to Neural Networks in Java, Second Edition, introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward, Hopfield, and Self Organizing Map networks are discussed. Training techniques such as Backpropagation, Genetic Algorithms and Simulated Annealing are also introduced. Practical examples are given for each neural network. Examples include the Traveling Salesman problem, handwriting recognition, financial prediction, game strategy, learning mathematical functions and special application to Internet bots. All Java source code can be downloaded online.
The Quest for Artificial Intelligence
Author: Nils J. Nilsson
Publisher: Cambridge University Press
ISBN: 1139642820
Pages:
Year: 2009-10-30
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Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
Practical Neural Network Recipies in C++
Author: Masters
Publisher: Elsevier
ISBN: 0080514332
Pages: 493
Year: 2014-06-28
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This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up. The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included. Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages.
An Intelligence in Our Image
Author: Osonde A. Osoba, William Welser IV
Publisher: Rand Corporation
ISBN: 0833097636
Pages: 44
Year: 2017-04-05
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Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.
Artificial Intelligence
Author: Nils J. Nilsson
Publisher: Morgan Kaufmann
ISBN: 1558605355
Pages: 513
Year: 1998
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This new book, by one of the most respected researchers in Artificial Intelligence, features a radical new 'evolutionary' organization that begins with low level intelligent behavior and develops complex intelligence as the book progresses.
Artificial Intelligence Simplified
Author: Binto George, Gail Carmichael
Publisher: CSTrends LLP
ISBN: 1944708022
Pages: 138
Year: 2016-01-08
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The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a “bridge” book, or as an introductory textbook. For students, there is a lower priced edition (ISBN 978-1944708016) of the same book. Published by CSTrends LLP.
Artificial Intelligence Safety and Security
Author: Roman V. Yampolskiy
Publisher: CRC Press
ISBN: 1351251368
Pages: 444
Year: 2018-07-27
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The history of robotics and artificial intelligence in many ways is also the history of humanity’s attempts to control such technologies. From the Golem of Prague to the military robots of modernity, the debate continues as to what degree of independence such entities should have and how to make sure that they do not turn on us, its inventors. Numerous recent advancements in all aspects of research, development and deployment of intelligent systems are well publicized but safety and security issues related to AI are rarely addressed. This book is proposed to mitigate this fundamental problem. It is comprised of chapters from leading AI Safety researchers addressing different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. The book is the first edited volume dedicated to addressing challenges of constructing safe and secure advanced machine intelligence. The chapters vary in length and technical content from broad interest opinion essays to highly formalized algorithmic approaches to specific problems. All chapters are self-contained and could be read in any order or skipped without a loss of comprehension.