handbook machine learning applications (27 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware - Artificial Intelligence is transforming the world faster than ever before, and the demand for skilled AI engineers continues to grow across every industry. Whether you are a beginner exploring artificial intelligence for the first time or a developer looking to expand your technical skills, AI Engineering Handbook provides a practical and easy to understand roadmap for mastering modern AI development.This comprehensive guide introduces the core foundations of AI engineering while helping readers build real world skills in machine learning, deep learning, generative AI, neural networks, prompt engineering, Python programming, and AI automation.Inside this book, you will learn how artificial intelligence systems work, how machine learning models are trained, and how AI engineers design intelligent applications used in today's technology driven world. From understanding data and algorithms to building AI powered applications, this handbook breaks down complex concepts into clear, practical lessons that are accessible for beginners and valuable for aspiring professionals.You will also explore the latest advancements in generative AI, large language models, AI assistants, and intelligent automation tools that are reshaping businesses and careers globally. With practical explanations and real world examples, this book equips you with the knowledge needed to confidently begin your journey in AI engineering.Inside This Book, You Will Discover: - Artificial Intelligence fundamentals explained in simple terms- Machine Learning and Deep Learning essentials- Python programming for AI development- Neural Networks and Generative AI concepts- Prompt Engineering and AI automation workflows- Real world AI applications and deployment basics- AI ethics, security, and responsible AI practices- Career guidance for future AI engineersBeginner friendly explanations with practical insightsWhether your goal is to become an AI engineer, machine learning developer, data scientist, software engineer, or technology entrepreneur, this book gives you the foundational knowledge and practical understanding needed to succeed in one of the world's fastest growing industries.If you are ready to explore the future of artificial intelligence, build valuable technical skills, and understand the technologies shaping tomorrow's digital world, then AI Engineering Handbook is the perfect place to begin.Start your AI journey today and discover how to build intelligent systems that can transform ideas into innovation.

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Paperback. Zustand: Brand New. 294 pages. 9.18x6.12x9.21 inches. In Stock.

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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 564 | Sprache: Englisch | Produktart: Bücher | This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation.The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.

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Taschenbuch. Zustand: Neu. Handbook of Machine Learning Applications for Genomics | Sanjiban Sekhar Roy (u. a.) | Taschenbuch | x | Englisch | 2023 | Springer | EAN 9789811691607 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 452 | Sprache: Englisch | Produktart: Bücher | In the modern data-driven era, artificial intelligence (AI) and machine learning (ML) technologies that allow a computer to mimic intelligent human behavior are essential for organizations to achieve business excellence and assist organizations in extracting useful information from raw data. AI and ML have existed for decades, but in the age of big data, this sort of analysis is in higher demand than ever, especially for customer support and analytics. The Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics investigates the applications of AI and ML and how they can be implemented to enhance customer support and analytics at various levels of organizations. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, deep learning, customer sentiment analysis, data mining, neural networks, and business analytics.

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Hardcover. Zustand: Brand New. 280 pages. 9.50x6.25x1.00 inches. In Stock.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians, practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields.

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Hardcover. Zustand: Brand New. 564 pages. 9.19x6.13x1.18 inches. In Stock.

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Paperback. Zustand: Brand New. 228 pages. 9.25x6.10x0.63 inches. In Stock.

Hardcover. Zustand: Brand New. 228 pages. 9.25x6.10x0.79 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 492 | Sprache: Englisch | Produktart: Bücher | Artificial intelligence is at the forefront of research and implementation in many industries including healthcare and agriculture. Whether it's detecting disease or generating algorithms, deep learning techniques are advancing exponentially. Researchers and professionals need a platform in which they can keep up with machine learning trends and their developments in the real world. The Handbook of Research on Applications and Implementations of Machine Learning Techniques provides innovative insights into the multi-disciplinary applications of machine learning algorithms for data analytics. The content within this publication examines disease identification, neural networks, and language support. It is designed for IT professionals, developers, data analysts, technology specialists, R&D professionals, industrialists, practitioners, researchers, academicians, and students seeking research on deep learning procedures and their enactments in the fields of medicine, engineering, and computer science.

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Hardcover. Zustand: gut. 2023. Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics In deutscher Sprache. pages.