Artificial Intelligence Foundations Machine Learning
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Artificial Intelligence Foundations Machine Learning
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Author :
language : en
Publisher:
Release Date : 2018
Artificial Intelligence Foundations Machine Learning written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Learn how to use machine learning to make better decisions and find patterns in your data.
Artificial Intelligence And Machine Learning Foundations
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Author : Andrew Lowe
language : en
Publisher: BCS, the Chartered Institute for IT
Release Date : 2024-10-28
Artificial Intelligence And Machine Learning Foundations written by Andrew Lowe and has been published by BCS, the Chartered Institute for IT this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-28 with Computers categories.
In alignment with BCS AI Foundation and Essentials certificates, this introductory guide provides the understanding you need to start building artificial intelligence (AI) capability into your organisation. You will learn how AI is being utilised today to support products, services, science and engineering, and how it is likely to be used in the future to balance the talents of humans and machines. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed. You will delve into the theory behind AI and machine learning projects, examining techniques for learning from data, the use of neural networks and why algorithms are so important in the development of a new AI agent or system.
Artificial Intelligence Foundations
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Author : Andrew Lowe
language : en
Publisher: BCS, The Chartered Institute for IT
Release Date : 2020-08-24
Artificial Intelligence Foundations written by Andrew Lowe and has been published by BCS, The Chartered Institute for IT this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-24 with categories.
In line with the BCS AI Foundation and Essentials certificates, this book guides you through the world of AI. You will learn how AI is being utilised today, and how it is likely to be used in the future. You will explore robotics and machine learning within the context of AI, and discover how the challenges AI presents are being addressed.
Artificial Intelligence Foundations Machine Learning
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Author : Doug Rose
language : en
Publisher:
Release Date : 2018
Artificial Intelligence Foundations Machine Learning written by Doug Rose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Engineering Mathematics And Artificial Intelligence
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Author : Herb Kunze
language : en
Publisher: CRC Press
Release Date : 2023-07-26
Engineering Mathematics And Artificial Intelligence written by Herb Kunze and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-26 with Computers categories.
The fields of Artificial Intelligence (AI) and Machine Learning (ML) have grown dramatically in recent years, with an increasingly impressive spectrum of successful applications. This book represents a key reference for anybody interested in the intersection between mathematics and AI/ML and provides an overview of the current research streams. Engineering Mathematics and Artificial Intelligence: Foundations, Methods, and Applications discusses the theory behind ML and shows how mathematics can be used in AI. The book illustrates how to improve existing algorithms by using advanced mathematics and offers cutting-edge AI technologies. The book goes on to discuss how ML can support mathematical modeling and how to simulate data by using artificial neural networks. Future integration between ML and complex mathematical techniques is also highlighted within the book. This book is written for researchers, practitioners, engineers, and AI consultants.
Ai Foundations Of Machine Learning
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Author : Jon Adams
language : en
Publisher: Green Mountain Computing
Release Date :
Ai Foundations Of Machine Learning written by Jon Adams and has been published by Green Mountain Computing this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
AI Foundations of Machine Learning Embark on a clarifying expedition through the vibrant world of AI with "AI Foundations of Machine Learning." This comprehensive guide is meticulously crafted for those eager to unravel the complex mechanisms driving artificial intelligence and for pioneers looking to grasp the foundational stones of future technological advancements. From the fundamentals to the futuristic prospects, this book serves as both an educational journey and an initiation into the realm where data, computation, and potential converge. Contents: Understanding Supervised Learning: Begin your journey with an exploration of supervised learning, where machines learn from data with known outcomes, setting the stage for further complexities. The Mechanics of Unsupervised Learning: Delve into the artistry of AI as it uncovers hidden patterns without explicit instructions, highlighting the autonomy of machine learning. Diving into Neural Networks: Uncover the intricacies of neural networks, AI's approximation of the human brain, capable of recognizing speech, images, and nuances in vast datasets. The Decision Tree Paradigm: Discover the decision-making processes of AI through the decision tree paradigm, where data is systematically divided and conquered. Ensemble Methods Combining Strengths: Learn about the power of ensemble methods, which combine multiple models to enhance predictive accuracy and overcome individual weaknesses. Evaluating Model Performance: Understand the critical aspect of evaluating AI model performance, ensuring the integrity and applicability of machine learning applications. Machine Learning in the Real World: Witness the transformative impact of machine learning across various industries, from healthcare to finance, and how it reshapes our interaction with technology. The Future of Machine Learning: Gaze into the future, anticipating the breakthroughs and challenges of machine learning as it becomes an omnipresent force in our lives. This book is your gateway to understanding and participating in the future of AI, equipped with the knowledge to navigate and contribute to the advancements that lie ahead. Whether you are a student, professional, or enthusiast, "AI Foundations of Machine Learning" offers valuable insights into the ever-evolving field of machine learning, encouraging readers to not only understand but also to innovate in the unfolding story of AI.
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges
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Author : Freddy Lécué
language : en
Publisher: SAGE Publications Limited
Release Date : 2020-05-06
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by Freddy Lécué and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-06 with Computers categories.
The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
Logical Foundations Of Artificial Intelligence
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Author : Michael R. Genesereth
language : en
Publisher: Morgan Kaufmann
Release Date : 1987
Logical Foundations Of Artificial Intelligence written by Michael R. Genesereth and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with COMPUTERS categories.
Intended both as a text for advanced undergraduates and graduate students, and as a key reference work for AI researchers and developers, Logical Foundations of Artificial Intelligence is a lucid, rigorous, and comprehensive account of the fundamentals of artificial intelligence from the standpoint of logic. The first section of the book introduces the logicist approach to AI--discussing the representation of declarative knowledge and featuring an introduction to the process of conceptualization, the syntax and semantics of predicate calculus, and the basics of other declarative representations such as frames and semantic nets. This section also provides a simple but powerful inference procedure, resolution, and shows how it can be used in a reasoning system. The next several chapters discuss nonmonotonic reasoning, induction, and reasoning under uncertainty, broadening the logical approach to deal with the inadequacies of strict logical deduction. The third section introduces modal operators that facilitate representing and reasoning about knowledge. This section also develops the process of writing predicate calculus sentences to the metalevel--to permit sentences about sentences and about reasoning processes. The final three chapters discuss the representation of knowledge about states and actions, planning, and intelligent system architecture. End-of-chapter bibliographic and historical comments provide background and point to other works of interest and research. Each chapter also contains numerous student exercises (with solutions provided in an appendix) to reinforce concepts and challenge the learner. A bibliography and index complete this comprehensive work.
Generative Ai Foundations Developments And Applications
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Author : Kannan, Rajkumar
language : en
Publisher: IGI Global
Release Date : 2025-03-26
Generative Ai Foundations Developments And Applications written by Kannan, Rajkumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Computers categories.
In recent years, the field of generative artificial intelligence (AI) has witnessed remarkable advancements, transforming various domains from art and music to language and healthcare. Advanced techniques, such as conditional generation, style transfer, and unsupervised learning, showcase the cutting-edge research shaping the field. The ability of generative AI models to create novel content autonomously has sparked immense interest and innovation. Future directions provide speculations for potential breakthroughs, challenges, and opportunities for further research and innovation. Generative AI Foundations, Developments, and Applications serves as a resource to understanding generative AI across various domains including natural language processing, computer vision, and drug discovery. It explores the theoretical foundations, latest developments, and practical applications of generative AI. Covering topics such as prompt engineering, multimodal data fusion, and natural language processing, this book is an excellent resource for computer scientists, computer engineers, practitioners, professionals, researchers, scholars, academicians, and more.
Explainable Ai Foundations Methodologies And Applications
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Author : Mayuri Mehta
language : en
Publisher: Springer Nature
Release Date : 2022-10-19
Explainable Ai Foundations Methodologies And Applications written by Mayuri Mehta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-19 with Technology & Engineering categories.
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas. The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.