A Concise Book Of Artificial Intelligence
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A Concise Book Of Artificial Intelligence
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Author : Sofiqul Islam
language : en
Publisher: Perfect Writer
Release Date : 2025-07-08
A Concise Book Of Artificial Intelligence written by Sofiqul Islam and has been published by Perfect Writer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-08 with Fiction categories.
A Concise Book of Artificial Intelligence" by Sofiqul Islam is a comprehensive guide designed for Class 10 students, aligned with the CBSE 2024–25 curriculum (Subject Code – 417). The book simplifies complex AI concepts into easy-to-understand lessons covering topics like AI project cycles, advanced Python, data science, computer vision, and natural language processing. It also includes employability skills, sample papers, and practical exercises, making it an ideal resource for students preparing for board exams and aiming to gain foundational knowledge in artificial intelligence.
Introduction To Artificial Intelligence
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Author : Wolfgang Ertel
language : en
Publisher: Springer
Release Date : 2018-01-18
Introduction To Artificial Intelligence written by Wolfgang Ertel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Computers categories.
This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.
A Concise Introduction To Multiagent Systems And Distributed Artificial Intelligence
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Author : Nikos Vlassis
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2007
A Concise Introduction To Multiagent Systems And Distributed Artificial Intelligence written by Nikos Vlassis and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.
The Essence Of Artificial Intelligence
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Author :
language : en
Publisher: Pearson Education India
Release Date :
The Essence Of Artificial Intelligence written by and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Artificial Intelligence
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Author : Melanie Mitchell
language : en
Publisher: Penguin UK
Release Date : 2019-10-15
Artificial Intelligence written by Melanie Mitchell and has been published by Penguin UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-15 with Computers categories.
'After reading Mitchell’s guide, you’ll know what you don’t know and what other people don’t know, even though they claim to know it. And that’s invaluable'' The New York Times A leading computer scientist brings human sense to the AI bubble No recent scientific enterprise has been so alluring, terrifying and filled with extravagant promise and frustrating setbacks as artificial intelligence. Writing with clarity and passion, leading AI researcher Melanie Mitchell offers a captivating account of modern-day artificial intelligence. Flavoured with personal stories and a twist of humour, Artificial Intelligence illuminates the workings of machines that mimic human learning, perception, language, creativity and common sense. Weaving together advances in AI with cognitive science and philosophy, Mitchell probes the extent to which today's 'smart' machines can actually think or understand, and whether AI even requires such elusive human qualities at all. Artificial Intelligence: A Guide for Thinking Humans provides readers with an accessible and clear-eyed view of the AI landscape, what the field has actually accomplished, how much further it has to go and what it means for all of our futures.
Contemporary Artificial Intelligence
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Author : Richard E. Neapolitan
language : en
Publisher: CRC Press
Release Date : 2012-08-25
Contemporary Artificial Intelligence written by Richard E. Neapolitan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-25 with Computers categories.
The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures of spacecrafts. Exploring these algorithms and applications, Contemporary Artificial Intelligence presents strong AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. One of the first AI texts accessible to students, the book focuses on the most useful problem-solving strategies that have emerged from AI. In a student-friendly way, the authors cover logic-based methods; probability-based methods; emergent intelligence, including evolutionary computation and swarm intelligence; data-derived logical and probabilistic learning models; and natural language understanding. Through reading this book, students discover the importance of AI techniques in computer science.
Machine Learning
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Author : Steven W. Knox
language : en
Publisher: John Wiley & Sons
Release Date : 2018-04-17
Machine Learning written by Steven W. Knox and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-17 with Computers categories.
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS PROSE Award Finalist 2019 Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field—presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection— essential elements of most applied projects. This important resource: Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods Presents R source code which shows how to apply and interpret many of the techniques covered Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions Contains useful information for effectively communicating with clients A volume in the popular Wiley Series in Probability and Statistics, Machine Learning: a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning. STEVEN W. KNOX holds a Ph.D. in Mathematics from the University of Illinois and an M.S. in Statistics from Carnegie Mellon University. He has over twenty years’ experience in using Machine Learning, Statistics, and Mathematics to solve real-world problems. He currently serves as Technical Director of Mathematics Research and Senior Advocate for Data Science at the National Security Agency.
The Executive Guide To Artificial Intelligence
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Author : Andrew Burgess
language : en
Publisher: Springer Nature
Release Date : 2024-06-30
The Executive Guide To Artificial Intelligence written by Andrew Burgess and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-30 with Business & Economics categories.
This book, now in a thoroughly revised and updated second edition, takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the book's core is a framework which describes, in nontechnical language, the nine core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through prediction, to Generative AI, is explained using real–life examples and how they can be applied in a business environment. The advent of Large Language Models has put AI front and centre of Board discussions. AI has the ability to deliver step–change benefits to organisations and enables forward–thinking business leaders to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive who wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in AI, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the AI and LLM hype. The knowledge and experience he has gained in advising them has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book, business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.
Artificial Intelligence
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Author : Blay Whitby
language : en
Publisher: The Rosen Publishing Group, Inc
Release Date : 2009-01-15
Artificial Intelligence written by Blay Whitby and has been published by The Rosen Publishing Group, Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-15 with Business & Economics categories.
Introduces artificial intelligence, what it can do, myths about it, and ways it may expand in the future.
Machine Learning Revised And Updated Edition
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Author : Ethem Alpaydin
language : en
Publisher: MIT Press
Release Date : 2021-08-17
Machine Learning Revised And Updated Edition written by Ethem Alpaydin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.
MIT presents a concise primer on machine learning—computer programs that learn from data and the basis of applications like voice recognition and driverless cars. No in-depth knowledge of math or programming required! Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don’t yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of “the new AI.” This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpaydin explains that as Big Data has grown, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. He covers: • The evolution of machine learning • Important learning algorithms and example applications • Using machine learning algorithms for pattern recognition • Artificial neural networks inspired by the human brain • Algorithms that learn associations between instances • Reinforcement learning • Transparency, explainability, and fairness in machine learning • The ethical and legal implicates of data-based decision making A comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming—making it accessible for everyday readers and easily adoptable for classroom syllabi.