Artificial Intelligence and Expert Systems. Techniques and Applications for Problem Solving

Mercury Learning and Information, I. Gupta, G. Nagpal

This book covers current AI applications and techniques for solving problems and accomplishing tasks. It introduces branches of AI such as formal logic, reasoning, knowledge engineering, expert systems, neural networks, and fuzzy logic. It emphasizes expert systems, with sections on state space search, knowledge engineering, neural networks, fuzzy logic, and Prolog.It begins with an introduction to AI and its applications, setting the stage for foundational concepts. Readers are guided through state space search and heuristic search strategies, crucial for problem-solving in AI. The focus shifts to expert systems, covering their development life cycle, knowledge acquisition, and representation, providing a deep dive into emulating human decision-making.Later chapters cover neural networks and the learning process, essential for creating adaptive systems. Sections on fuzzy logic and fuzzy systems introduce methods for handling uncertainty in AI. Final chapters on programming in logic and advanced Prolog offer practical techniques for AI solutions. This approach equips readers with the skills to apply AI in various domains, enhancing their problem-solving abilities and understanding of intelligent systems.

Artificial Intelligence Basics. A Self-Teaching Introduction

Mercury Learning and Information, N. Gupta, R. Mangla

This book is designed as a self-teaching introduction to the fundamental concepts of artificial intelligence (AI). It begins with the history of AI, the Turing test, and early applications, providing a strong foundation. Later chapters cover the basics of searching, game playing, and knowledge representation. The journey continues with detailed explorations of expert systems and machine learning, equipping readers with essential AI techniques.As the course progresses, you will delve into separate programming chapters on Prolog and Python, learning how to implement AI concepts in these languages. These chapters offer practical coding experience, enhancing your understanding of AI programming. The book culminates with a comprehensive chapter on AI machines and robotics, showcasing numerous modern applications and providing a glimpse into the future of AI technology.Understanding these AI concepts is crucial as they form the basis of many modern technologies and applications. This book ensures a smooth transition from a beginner to a proficient AI practitioner, equipped with both theoretical knowledge and practical skills. By the end of the book, you will have a thorough understanding of AI's history, core principles, and practical implementations, ready to apply this knowledge to real-world problems and projects.

Artificial Intelligence Engines. A Tutorial Introduction to the Mathematics of Deep Learning

James V Stone

This book is a comprehensive guide to the mathematics behind artificial intelligence engines, taking readers from foundational concepts to advanced applications. It begins with an introduction to artificial neural networks, exploring topics like perceptrons, linear associative networks, and gradient descent. Practical examples accompany each chapter, making complex mathematical principles accessible, even for those with limited prior knowledge.The book's detailed structure covers key algorithms like backpropagation, Hopfield networks, and Boltzmann machines, advancing to deep restricted Boltzmann machines, variational autoencoders, and convolutional neural networks. Modern topics such as generative adversarial networks, reinforcement learning, and capsule networks are explored in depth. Each section connects theory to real-world AI applications, helping readers understand how these techniques are used in practice.Ideal for students, researchers, and AI enthusiasts, the book balances theoretical depth with practical insights. Basic mathematical knowledge or foundation is recommended, allowing readers to fully engage with the content. This book serves as an accessible yet thorough resource for anyone eager to dive deeper into artificial intelligence and machine learning.

Artificial Intelligence in the 21st Century. The Future of Technology and Human Innovation

Mercury Learning and Information, Stephen Lucci, Sarhan M. Musa, Danny Kopec

This third edition provides a comprehensive, accessible presentation of AI, including examples, applications, full-color images, and human interest boxes. New chapters on deep learning, AI security, and AI programming keep the content cutting-edge. Topics like neural networks, genetic algorithms, natural language processing, planning, and complex board games are covered.The course starts with an AI overview, moving through uninformed search, intelligent search methods, and game-based strategies. It delves into logic in AI, knowledge representation, production systems, uncertainty in AI, and expert systems. Middle chapters cover machine learning, neural networks, and deep learning. It continues with nature-inspired search methods, natural language processing, and automated planning, ending with robotics and advanced computer games.These AI concepts are crucial for developing sophisticated AI applications. This book transitions you from novice to proficient AI practitioner, equipped with practical skills and comprehensive knowledge. Companion files with resources, simulations, and figures enhance learning. By the end, you'll understand AI principles and applications, ready to tackle real-world challenges.

Artificial Intelligence, Machine Learning, and Deep Learning. A Practical Guide to Advanced AI Techniques

Mercury Learning and Information, Oswald Campesato

This book introduces AI, then explores machine learning, deep learning, natural language processing (NLP), and reinforcement learning. Readers learn about classifiers like logistic regression, k-NN, decision trees, random forests, and SVMs. It delves into deep learning architectures such as CNNs, RNNs, LSTMs, and autoencoders, with Keras-based code samples supplementing the theory.Starting with a foundational AI overview, the course progresses into machine learning, explaining classifiers and their applications. It continues with deep learning, focusing on architectures like CNNs and RNNs. Advanced topics include LSTMs and autoencoders, essential for modern AI. The book also covers NLP and reinforcement learning, emphasizing their importance.Understanding these concepts is vital for developing advanced AI systems. This book transitions you from beginner to proficient AI practitioner, combining theoretical knowledge and practical skills. Appendices on Keras, TensorFlow 2, and Pandas enrich the learning experience. By the end, readers will understand AI principles and be ready to apply them in real-world scenarios.

Augmented Reality for Android Application Development. As an Android developer, including Augmented Reality (AR) in your mobile apps could be a profitable new string to your bow. This tutorial takes you through every aspect of AR for Android with lots of hands-on exercises

Dr. Raphael Grasset, Jens Grubert

Augmented Reality offers the magical effect of blending the physical world with the virtual world, which brings applications from your screen into your hands. AR redefines advertising and gaming, as well as education. It will soon become a technology that will have to be mastered as a necessity by mobile application developers.Augmented Reality for Android Application Development enables you to implement sensor-based and computer vision-based AR applications on Android devices. You will learn about the theoretical foundations and practical details of implemented AR applications, and you will be provided with hands-on examples that will enable you to quickly develop and deploy novel AR applications on your own.Augmented Reality for Android Application Development will help you learn the basics of developing mobile AR browsers, how to integrate and animate 3D objects easily with the JMonkeyEngine, how to unleash the power of computer vision-based AR using the Vuforia AR SDK, and will teach you about popular interaction metaphors. You will get comprehensive knowledge of how to implement a wide variety of AR apps using hands-on examples.This book will make you aware of how to use the AR engine, Android layout, and overlays, and how to use ARToolkit. Finally, you will be able to apply this knowledge to make a stunning AR application.

Azure OpenAI Essentials. A practical guide to unlocking generative AI-powered innovation with Azure OpenAI

Amit Mukherjee, Adithya Saladi, Marco Casalaina

Find out what makes Azure OpenAI a robust platform for building AI-driven solutions that can transform how businesses operate. Written by seasoned experts from Microsoft, this book will guide you in understanding Azure OpenAI from fundamentals through to advanced concepts and best practices.The book begins with an introduction to large language models (LLMs) and the Azure OpenAI Service, detailing how to access, use, and optimize its models. You'll learn how to design and implement AI-driven solutions, such as question-answering systems, contact center analytics, and GPT-powered search applications. Additionally, the chapters walk you through advanced concepts, including embeddings, fine-tuning models, prompt engineering, and building custom AI applications using LangChain and Semantic Kernel. You'll explore real-world use cases such as QnA systems, document summarizers, and SQLGPT for database querying, as well as gain insights into securing and operationalizing these solutions in enterprises.By the end of this book, you'll be ready to design, develop, and deploy scalable AI solutions, ensuring business success through intelligent automation and data-driven insights.

Azymut na AI. Jak obrać najlepszy kierunek?

Chris Badura

Rewolucja już tu jest Decyzja, by napisać tę książkę, wzięła się z przekonania jej autora, że w sercu każdej technologii powinien się znajdować człowiek: jego potrzeby, emocje i marzenia. Drugim powodem było pragnienie nakreślenia ogromu perspektyw, jakie otwiera przed nami sztuczna inteligencja. I nie chodzi tu tylko o możliwości techniczne. Także o to, że AI zaprasza ludzi do świata, w którym maszyny rozumieją ich lepiej niż kiedykolwiek przedtem. Rewolucja AI właśnie się rozpoczyna, dobrze jest się do niej zawczasu przygotować - zarówno mentalnie, jak i zawodowo. Zacznij czytać i przekonaj się, w jaki sposób sztuczna inteligencja kształtuje teraźniejszość i przyszłość w różnych aspektach życia: od rewolucyjnych zmian w edukacji, poprzez przełomowe zastosowania w medycynie, aż po wyjątkowe innowacje w sztuce i designie. Zrozum, jak działa sztuczna inteligencja Dowiedz się, w jakich dziedzinach życia wspomaga nas już dziś Naucz się z nią komunikować Poznaj zawody, w których współpraca z AI będzie wkrótce odgrywała kluczową rolę Zobacz, jak za przyczyną sztucznej inteligencji zmieni się świat