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Links to Free Computer, Mathematics, Technical Books all over the World



The Amazing Journey of Reason: from DNA to Artificial Intelligence
This book analyses the evolution of complex structures (Organisms, or organized, living, systems) in the universe  from the subatomic particles after the Big Bang onwards  in order to understand the emergence of today's interconnected society.

AI Art: Machine Visions and Warped Dreams (Joanna Zylinska)
The book critically examines artworks that use AI, be it in the form of visual style transfer, algorithmic experiment or critical commentary. It also engages with their predecessors, including robotic art and net art.

AI Crash Course (Hadelin de Ponteves)
This book teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. It gives you everything you need to build AI systems with reinforcement learning and deep learning.

AI based Robot Safe Learning and Control (Xuefeng Zhou, et al)
This book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning.

On the Path to AI: Foundations of the Machine Learning Age
This book explores machine learning and its impact on how we make sense of the world. It introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data.

Artificial Intelligence: Computational Agents, 2nd Edition
This text is a modern and coherent introduction to the field of Artificial Intelligence that uses rational computational agents and logic as unifying threads in this vast field. Many fully worked out examples, expanded coverage on machine learning material, etc.

The Age of Intelligent Machines (Ray Kurzweil)
This book probes the past, present, and future of artificial intelligence, from its earliest philosophical and mathematical roots to tantalizing glimpses of 21stcentury machines with superior intelligence and truly prodigious speed and memory.

New Applications of Artificial Intelligence (Pedro Ponce, et al)
This book shows the newest applications reached according with the technological changes that are presented nowadays. Those changes drastically appear in digital systems or other parallel areas that allow to improve the performance of AI algorithms.

Artificial Intelligence for Big Data (Anand Deshpande, et al)
You will learn to use machine learning algorithms such as kmeans, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of machine and deep learning techniques to work on genetic and neurofuzzy algorithms.

Artificial Intelligence: Structures and Strategies (George F. Luger)
This book captures the essence of artificial intelligence  solving the complex problems that arise wherever computer technology is applied. Readers learn how to use a number of different software tools and techniques to address many challenges.

Paradigms of Artificial Intelligence Programming: Case Studies
This book is an overview of classical artificial intelligence (AI) programming via actual implementation of landmark systems (case studies). It teaches advanced Common Lisp techniques in the context of building major AI systems.

Computers and Thought: An Introduction to Artificial Intelligence
This book provides a unified, selfcontained introduction to artificial intelligence for readers with little or no computing background. It presents an original extended AI programming project  the Automated Tourist Guide exercise throughout the main chapters of the text to illustrate the material covered and show how AI actually works.

AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java
This book illustrates how to program AI algorithms in Lisp, Prolog, and Java. The book basically cover each topic 3 times in each language. Topics include: simple productionlike system based on logic, logicbased learning, and natural language parsing.

Pattern Recognition and Machine Learning (Christopher Bishop)
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible.

Practical Artificial Intelligence Programming in Java (Mark Watson)
This book uses both best of breed open source software and the author's own libraries to introduce the reader to Artificial Intelligence (AI) technologies like genetic algorithms, neural networks, expert systems, machine learning, etc.

The Quest for Artificial Intelligence: Ideas and Achievements
This book traces the history of the subject, from the early dreams of eighteenthcentury (and earlier) pioneers to the more successful work of today's AI engineers  the definitive history of a field that has captivated the imaginations of scientists, philosophers, etc.

Building the Second Mind 1956: The Origins of Artificial Intelligence
This book tells the history of the origins of Artificial Intelligence (AI). As the field that seeks to do things that would be considered intelligent if a human being did them, AI is a constant of human thought.

Building the Second Mind, 19611980: Commercial Expert Systems
This book tells the story of the development, during the 1960s and 1970s, of AI, the field that sought to get computers to do things that would be considered intelligent if a person did them. Watching advances of the 1960s and 1970s by the efforts of AI founders.

Clever Algorithms: NatureInspired Programming Recipes
The book describes 45 algorithms from the field of Artificial Intelligence. All algorithm descriptions are complete and consistent to ensure that they are accessible, usable and understandable by a wide audience.

The Future of Machine Intelligence (David Beyer)
This exclusive report unpacks concepts and innovations that represent the frontiers of eversmarter machines. You’ll get a rare glimpse into this exciting field through the eyes of some of its leading minds.

Artificial Intelligence: Foundations of Computational Agents
This is a a textbook aimed at junior to senior undergraduate students and firstyear graduate students. It presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents.

The LION Way: Machine Learning Plus Intelligent Optimization
This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to people in both fields. Optimization approaches have enjoyed prominence in machine learning.

Modeling Creativity  Case Studies in Python (Tom De Smedt)
This book is to model creativity using computational approaches in Python. The aim is to construct computer models that exhibit creativity in an artistic context, that is, that are capable of generating or evaluating an artwork (visual or linguistic), etc.

Simply Logical: Intelligent Reasoning by Example (Peter Flach)
This book is an introduction to Prolog programming for artificial intelligence covering both basic and advanced AI material. A unique advantage to this work is the combination of AI, Prolog and Logic.

Inductive Logic Programming: Techniques and Applications
This book is an introduction to inductive logic programming (ILP), which aims at a formal framework as well as practical algorithms for inductively learning relational descriptions in the form of logic programs.

Introduction to Soft Computing (Eva Volna)
This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.

Learning Deep Architectures for AI (Yoshua Bengio)
This book discusses the motivations for and principles of learning algorithms for deep architectures. By analyzing and comparing recent results with different learning algorithms for deep architectures, explanations for their success are proposed.

Reinforcement Learning: An Introduction, Second Edition
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.

Logic Programming in Scheme (Nils M. Holm)
Questions answered in this little book: What is logic programming? Why is negation hard in logic programming? What is cutting? How do I solve logic puzzles? How is logic programming implemented?

Expert Systems in Prolog (Dennis Merritt)
For Prolog programmer interested in either building expert systems or experimenting with various expert system techniques. using a stepbystep approach to building systems, explaining the concepts and showing the Prolog code at each stage.

From Bricks to Brains: Embodied Cognitive Science of LEGO Robots
This book introduces embodied cognitive science and illustrates its foundational ideas through the construction and observation of LEGO Mindstorms robots  even simple agents, such as LEGO robots, are capable of exhibiting complex behavior.

Mind, Body, World: Foundations of Cognitive Science (M. Dawson)
Intended to introduce the foundations of cognitive science, this book addresses a number of questions currently being asked by those practicing in the field of cognitive science. It highlights the fundamental tensions and lines of fragmentation of cognitive science.

Planning Algorithms (Steven M. LaValle)
This is the only book for teaching and referencing of Planning Algorithms in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications and medicine, etc.

Artificial Intelligence and Molecular Biology (Lawrence Hunter)
A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. They are the first to treat the computational needs of the biology community handinhand with appropriate advances in artificial intelligence.

A Field Guide to Genetic Programming (Riccardo Poli, et al)
This book to provides a complete and coherent review of the theory of Genetic Programming (GP). This unique overview of this exciting technique is written by three of the most active scientists in GP.

Genetic Programming  New Approaches and Successful Applications
The purpose of this book is to show recent advances in the field of GP, both the development of new theoretical approaches and the emergence of applications that have successfully solved different real world problems.

Fuzzy Logic  Emerging Technologies and Applications (E. P. Dadios)
This book shows various applications of Fuzzy Logic in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems.

Genetic Algorithms in Applications (Rustem Popa)
This wellorganized book takes the reader through the new and rapidly expanding field of genetic algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications.

BioInspired Computational Algorithms and Their Applications
Integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many realworld problems.

An Introduction to Logic Programming Through Prolog (J. M. Spivey)
This is one of the few texts that combines three essential theses in the study of logic programming: logic, programming, and implementation.

Common LISP: A Gentle Introduction to Symbolic Computation
This highly accessible introduction to Lisp is suitable both for novices approaching their first programming language and experienced programmers interested in exploring a key tool for artificial intelligence research.

A Quick and Gentle Guide to Constraint Logic Programming
This is an introductory and downtoearth presentation of Constraint Logic Programming (CLP), for solving combinatorial as well as continuous constraint satisfaction problems and constraint optimization problems.

Conceptive C (Harry McGeough)
Conceptive C is an AI programming Language based on ObjectiveC and C Language. It is a superset of both languages and is designed to work with Apple Mac OS X and iOS.

Essentials of Metaheuristics (Sean Luke)
This book is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other nonexperts.

Shape Interrogation for Computer Aided Design and Manufacturing
This book provides the mathematical fundamentals as well as algorithms for various shape interrogation methods including nonlinear polynomial solvers, intersection problems, differential geometry of intersection curves, distance functions, etc.

Machine Learning, Neural and Statistical Classification (D. Michie)
Statistical, machine learning and neural network approaches to classification are all covered in this volume.

Machine Learning Using C# Succinctly (James McCaffrey)
This book shows several different approaches to applying machine learning to data analysis and prediction problems. It also demonstrates different clustering and classification techniques, and explains how effective these techniques can be.

A Course in Machine Learning (Hal Daum� III)
This is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).

Global Optimization Algorithms  Theory and Application. 2nd Edition
This book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems.

Recent Advances in Face Recognition (Kresimir Delac, et al)
This book provides a broad overview on face recognition and identified trends for future developments and the means for implementing robust systems..

Logic, Programming and Prolog, 2nd Edition (Ulf Nilsson, et al)
This book introduces major new developments in a continually evolving field and includes such topics as concurrency and equational and constraint logic programming.

Logic for Computer Science: Automatic Theorem Proving
This book introduces mathematical logic with an emphasis on proof theory and procedures for algorithmic construction of formal proofs. It is useful for the formalization of proofs and basics of automatic theorem proving.

Eye, Brain, and Vision (David H. Hubel)
This book brings you to the edge of current knowledge about vision, and explores the tasks scientists face in deciphering the many remaining mysteries of vision and the workings of the human brain.