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Fundamentals Of The New Artificial Intelligence
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Book Synopsis Fundamentals of the New Artificial Intelligence by : Toshinori Munakata
Download or read book Fundamentals of the New Artificial Intelligence written by Toshinori Munakata and published by Springer Science & Business Media. This book was released on 2008-01-01 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.
Book Synopsis Fundamentals of Artificial Intelligence by : K.R. Chowdhary
Download or read book Fundamentals of Artificial Intelligence written by K.R. Chowdhary and published by Springer Nature. This book was released on 2020-04-04 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Artificial Intelligence introduces the foundations of present day AI and provides coverage to recent developments in AI such as Constraint Satisfaction Problems, Adversarial Search and Game Theory, Statistical Learning Theory, Automated Planning, Intelligent Agents, Information Retrieval, Natural Language & Speech Processing, and Machine Vision. The book features a wealth of examples and illustrations, and practical approaches along with the theoretical concepts. It covers all major areas of AI in the domain of recent developments. The book is intended primarily for students who major in computer science at undergraduate and graduate level but will also be of interest as a foundation to researchers in the area of AI.
Book Synopsis Artificial Intelligence and Machine Learning Fundamentals by : Zsolt Nagy
Download or read book Artificial Intelligence and Machine Learning Fundamentals written by Zsolt Nagy and published by Packt Publishing Ltd. This book was released on 2018-12-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Book Synopsis Artificial Intelligence by : Cherry Bhargava
Download or read book Artificial Intelligence written by Cherry Bhargava and published by CRC Press. This book was released on 2021-07-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference text discusses the fundamental concepts of artificial intelligence and its applications in a single volume. Artificial Intelligence: Fundamentals and Applications presents a detailed discussion of basic aspects and ethics in the field of artificial intelligence and its applications in areas, including electronic devices and systems, consumer electronics, automobile engineering, manufacturing, robotics and automation, agriculture, banking, and predictive analysis. Aimed at senior undergraduate and graduate students in the field of electrical engineering, electronics engineering, manufacturing engineering, pharmacy, and healthcare, this text: Discusses advances in artificial intelligence and its applications. Presents the predictive analysis and data analysis using artificial intelligence. Covers the algorithms and pseudo-codes for different domains. Discusses the latest development of artificial intelligence in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. Covers the applications of artificial intelligence in fields, including pharmacy and healthcare, electronic devices and systems, manufacturing, consumer electronics, and robotics.
Book Synopsis Understanding Artificial Intelligence by : Albert Chun-Chen Liu
Download or read book Understanding Artificial Intelligence written by Albert Chun-Chen Liu and published by John Wiley & Sons. This book was released on 2022-09-21 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different???many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectors Traces the history of neural networks and explains popular neural network architectures Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV) Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU) Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.
Book Synopsis Fundamentals of Deep Learning by : Nikhil Buduma
Download or read book Fundamentals of Deep Learning written by Nikhil Buduma and published by "O'Reilly Media, Inc.". This book was released on 2017-05-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning
Book Synopsis Fundamentals of Machine Learning for Predictive Data Analytics, second edition by : John D. Kelleher
Download or read book Fundamentals of Machine Learning for Predictive Data Analytics, second edition written by John D. Kelleher and published by MIT Press. This book was released on 2020-10-20 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
Book Synopsis Fundamentals of Machine Learning by : Thomas Trappenberg
Download or read book Fundamentals of Machine Learning written by Thomas Trappenberg and published by Oxford University Press. This book was released on 2019-11-28 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in machine learning is exploding worldwide, both in research and for industrial applications. Machine learning is fast becoming a fundamental part of everyday life. This book is a brief introduction to this area - exploring its importance in a range of many disciplines, from science to engineering, and even its broader impact on our society. The book is written in a style that strikes a balance between brevity of explanation, rigorous mathematical argument, and outlines principle ideas. At the same time, it provides a comprehensive overview of a variety of methods and their application within this field. This includes an introduction to Bayesian approaches to modeling, as well as deep learning. Writing small programs to apply machine learning techniques is made easy by high level programming systems, and this book shows examples in Python with the machine learning libraries 'sklearn' and 'Keras'. The first four chapters concentrate on the practical side of applying machine learning techniques. The following four chapters discuss more fundamental concepts that includes their formulation in a probabilistic context. This is followed by two more chapters on advanced models, that of recurrent neural networks and that of reinforcement learning. The book closes with a brief discussion on the impact of machine learning and AI on our society. Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to students and researchers across computer science and computational neuroscience, as well as the broader cognitive sciences.
Book Synopsis Artificial Intelligence by : Tim D. Washington
Download or read book Artificial Intelligence written by Tim D. Washington and published by Independently Published. This book was released on 2019-02-27 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is Artificial Intelligence? Artificial intelligence is a system that tends to simulate intelligent behaviors into computer-controlled machines or digital computers. Artificial Intelligence normally gives a machine the ability to carry out tasks usually associated with intelligent beings like us. Some of these tasks include translating languages, decision-making, visual perception, and speech recognition. In simple terms, artificial intelligence is the capability of any machine to mimic intelligent human behavior. Contrary to what many may think, Artificial intelligence is not a new field of study. In fact, it is older than most millennials reading this guide now. This may make you wonder when the concept of AI really started and from whence it came. As you will learn, machine learning is going to be a big deal in the world of technology. Those who would have started using it to unlock their data will greatly benefit from it even before people realize it exists. As a smart person, you should use this book to familiarize yourself with how machine learning works and then learn how to use it to your advantage. These days, AI is associated with the high-tech companies that dominate the field. Artificial intelligence first started as an academic discipline, but it has since sunken its tendrils into the business sector. Many AI researchers have abandoned academia altogether and flocked to companies like Facebook, Microsoft, Alphabet (Google) Amazon, openAI, and so on. The said companies are all working on different machine learning algorithms and are without a doubt at the forefront of AI research. Those with advanced degrees in AI, computer science, and maths rather join the engineering teams of these companies than stay in the academia. And since they are at the bleeding edge, it is worth listening to what their leaders have to say. Some have been quiet on the concerns about AI, and others like Amazon's Bezos have said that they aren't worried about potential AI threats. But, other visionaries like Bill Gates, Elon Musk, and physicist Stephen Hawking have all voiced their opinions on the potential dangers of Artificial Intelligence. In January 2015, Hawking, Musk, and several other AI experts signed an open letter on artificial intelligence research, calling for increased study on the potential effects on society. The twelve-page document is entitled "Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter". It calls for further research on new AI legislation, privacy, ethics research, and several other concerns. As described in the letter, the potential threats of artificial intelligence can fall into multiple dimensions. The good news is that the early stages of AI development that we find ourselves in are malleable. The future is ours to create, provided that proper time and care go into the non-engineering side of AI research and policy. Book Outline: Chapter 1 - Artificial Beings, a Brief History of the Human Psyche Chapter 2 - Top Six AI Myths Chapter 3 - Why AI is the New Business Degree Chapter 4 - Understanding Machine Learning Chapter 5 - Machine Learning Steps Chapter 6 - Robotics Chapter 7 - Natural Language Processing
Book Synopsis Artificial Intelligence with Common Lisp by : James L. Noyes
Download or read book Artificial Intelligence with Common Lisp written by James L. Noyes and published by Jones & Bartlett Learning. This book was released on 1992 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: [The book] provides a balanced survey of the fundamentals of artificial intelligence, emphasizing the relationship between symbolic and numeric processing. The text is structured around an innovative, interactive combination of LISP programming and AI; it uses the constructs of the programming language to help readers understand the array of artificial intelligence concepts presented. After an overview of the field of artificial intelligence, the text presents the fundamentals of LISP, explaining the language's features in more detail than any other AI text. Common Lisp is then used consistently, in both programming exercises and plentiful examples of actual AI code.- Back cover This text is intended to provide an introduction to both AI and LISp for those having a background in computer science and mathematics. -Pref.
Book Synopsis An Introductory Guide to Artificial Intelligence for Legal Professionals by : Juan Pavón
Download or read book An Introductory Guide to Artificial Intelligence for Legal Professionals written by Juan Pavón and published by Kluwer Law International B.V.. This book was released on 2020-05-14 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of very large data sets and the increase in computing power to process them has led to a renewed intensity in corporate and governmental use of Artificial Intelligence (AI) technologies. This groundbreaking book, the first devoted entirely to the growing presence of AI in the legal profession, responds to the necessity of building up a discipline that due to its novelty requires the pooling of knowledge and experiences of well-respected experts in the AI field, taking into account the impact of AI on the law and legal practice. Essays by internationally known expert authors introduce the essentials of AI in a straightforward and intelligible style, offering jurists as many practical examples and business cases as possible so that they are able to understand the real application of this technology and its impact on their jobs and lives. Elements of the analysis include the following: crucial terms: natural language processing, machine learning and deep learning; regulations in force in major jurisdictions; ethical and social issues; labour and employment issues, including the impact that robots have on employment; prediction of outcome in the legal field (judicial proceedings, patent granting, etc.); massive analysis of documents and identification of patterns from which to derive conclusions; AI and taxation; issues of competition and intellectual property; liability and responsibility of intelligent systems; AI and cybersecurity; AI and data protection; impact on state tax revenues; use of autonomous killer robots in the military; challenges related to privacy; the need to embrace transparency and sustainability; pressure brought by clients on prices; minority languages and AI; danger that the existing gap between large and small businesses will further increase; how to avoid algorithmic biases when AI decides; AI application to due diligence; AI and non-disclosure agreements; and the role of chatbots. Interviews with pioneers in the field are included, so readers get insights into the issues that people are dealing with in day-to-day actualities. Whether conceiving AI as a transformative technology of the labour market and training or an economic and business sector in need of legal advice, this introduction to AI will help practitioners in tax law, labour law, competition law and intellectual property law understand what AI is, what it serves, what is the state of the art and the potential of this technology, how they can benefit from its advantages and what are the risks it presents. As the global economy continues to suffer the repercussions of a framework that was previously fundamentally self-regulatory, policymakers will recognize the urgent need to formulate rules to properly manage the future of AI.
Book Synopsis Artificial Intelligence Basics by : Tom Taulli
Download or read book Artificial Intelligence Basics written by Tom Taulli and published by Apress. This book was released on 2019-08-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.
Book Synopsis Artificial Intelligence Fundamentals for Business Leaders by : I. Almeida
Download or read book Artificial Intelligence Fundamentals for Business Leaders written by I. Almeida and published by Now Next Later AI. This book was released on 2023-06 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2024 Edition. Free access to the AI Academy! The perfect guide to help non-technical business leaders understand the power of AI. Completely up to date with the latest advancements in generative AI. Part of the Byte-sized Learning AI series by Now Next Later AI, these books break down complex concepts into easily digestible pieces, providing you with a solid foundation in the fundamentals of AI. More Than a Book By purchasing this book, you will also be granted free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. You will also receive free modules and 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion. AI Academy by Now Next Later AI We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically. Book and Course Learning Rubric - Chapters 1-7: Understanding of AI [11%] —Demonstrated comprehension of AI's evolution, definition, applications, and comparison with human intelligence. - Chapters 8-13: Understanding of Data and Data Management [11%] — Clear understanding of the significance of big data, and strategies for data management. - Chapters 14-29: Understanding of Machine Learning [30%] — Familiarity with machine learning algorithms, different learning types, and the key steps involved in a machine learning project. - Chapters 30-35: Understanding of Deep Learning [9%] — Understanding of deep learning, its basics, and the structure and types of neural networks. - Chapters 36-40: Understanding of Model Selection and Evaluation [9%] — Ability to select and evaluate machine learning models and utilize them for decision-making. - Chapters 41-50: Understanding of Generative AI [15%] — Detailed understanding of generative AI, its value chain, models, prompt strategies, applications, opportunities, and governance challenges. Assignment: Practical Application [15%] — Ability to apply generative AI understanding to real-world business challenges, demonstrating critical thinking and strategic planning skills.
Book Synopsis Fundamentals of Artificial Intelligence by : W. Bibel
Download or read book Fundamentals of Artificial Intelligence written by W. Bibel and published by Springer. This book was released on 1986 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the elaborated and harmonized versions of seven lectures given at the first Advanced Course in Artificial Intelligence, held in Vignieu, France, in July 1985. Most of them were written in tutorial form; the book thus provides an extremely valuable guide to the fundamental aspects of AI. In the first part, Delgrande and Mylopoulos discuss the concept of knowledge and its representation. The second part is devoted to the processing of knowledge. The contribution by Huet shows that both computation and inference or deduction are just different aspects of the same phenomenon. The chapter written by Stickel gives a thorough and knowledgeable introduction to the most important aspects of deduction by some form of resolution. The kind of reasoning that is involved in inductive inference problem solving (or programming) from examples, and in learning, is covered by Biermann. The tutorial by Bibel covers the more important forms of knowledge processing that might play a significant role in common sense reasoning. The third part of the book focuses on logic programming and functional programming. Jorrand presents the language FP2, where term rewriting forms the basis for the semantics of both functional and parallel programming. In the last chapter, Shapiro gives an overview of the current state of concurrent PROLOG.
Book Synopsis Fundamentals of Artificial Intelligence by :
Download or read book Fundamentals of Artificial Intelligence written by and published by . This book was released on 2019 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Stuart Russell Publisher :Createspace Independent Publishing Platform ISBN 13 :9781537600314 Total Pages :626 pages Book Rating :4.6/5 (3 download)
Book Synopsis Artificial Intelligence by : Stuart Russell
Download or read book Artificial Intelligence written by Stuart Russell and published by Createspace Independent Publishing Platform. This book was released on 2016-09-10 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Book Synopsis Artificial Intelligence for Intelligent Systems by : Inam Ullah Khan
Download or read book Artificial Intelligence for Intelligent Systems written by Inam Ullah Khan and published by CRC Press. This book was released on 2024-07-31 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic. This book: Provides a better understanding of artificial intelligence-based applications for future smart cities Presents a detailed understanding of artificial intelligence tools for intelligent technologies Showcases intelligent computing technologies in obtaining optimal solutions using artificial intelligence Discusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs) Covers machine learning-based Intrusion detection system (IDS) for smart grid It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.
