Machine learning principles applications (49 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware.

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paperback. Zustand: New. Paperback.Pub Date:2021-09-01 Pages:212 Language:Chinese Publisher:Machinery Industry Press Machine Learning Principles and Applications focuses on machine learning and its algorithms. and introduces its theoretical details and application methods in detail. Machine Learning Principles and Applications has 19 chapters. which introduce the overview of machine learning. linear regression and maximum entropy model. k-nearest neighbor algorithm. decision tree model. naive Bayes classifier. suppor.…

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paperback. Zustand: New. Paperback. Pub Date: 2025-01 Pages: 251 Publisher: Posts & Telecom Press This book is an introductory textbook for machine learning. explaining the principles and applications of mainstream machine learning algorithms. The book focuses on a deep and systematic explanation of the principles of classic machine learning algorithms such as linear regression. logistic regression. Naive Bayes. K-nearest neighbors. decision trees. support vector machines. K-means clustering. Gaussian mixture models.…

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Taschenbuch. Zustand: Neu. MACHINE LEARNING | PRINCIPLES AND ITS APPLICATIONS | A. Gnana Soundari (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204751665 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

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Taschenbuch. Zustand: Neu. Machine Learning and Analytics in Healthcare Systems | Principles and Applications | Himani Bansal (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9780367564865 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Signal Processing and Biomedical Engineering Research: Applications of Machine Learning Based on Big Data Principles contains expanded versions of selected contributions from the 2024 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB 2024) held at Temple University. The symposium covers a wide range of topics in the life sciences and promotes machine learning and big data applications in bioengineering. The topics covered include signal and image analysis (e.g., EEG, ECG, MRI), machine learning, data mining, and classification, big data resources and applications, applications of quantum computing, digital pathology, computational biology, and genomics, genetics, and proteomics. The book features detailed review articles, tutorials, and examples of successful applications that will appeal to professionals and researchers in signal processing, medicine, and biology. It also provides an easy-to-understand introduction to various bioengineering topics for students and professionals new to the field, and essential algorithmic details on valuable benchmarks for professionals active in the field.…

Hardback. Zustand: New. An expert compilation of on-device training techniques, regulatory frameworks, and ethical considerations of TinyML design and development In Tiny Machine Learning: Design Principles and Applications, a team of distinguished researchers delivers a comprehensive discussion of the critical concepts, design principles, applications, and relevant issues in Tiny Machine Learning (TinyML). Expert contributors introduce a new low power resource, offering vast applications in IoT devices with system-algorithm co-design. Tiny Machine Learning explores TinyML paradigms and enablers, TinyML for anomaly detection, and the learning panorama under TinyML. Readers will find explanations of TinyML devices and tools, power consumption and memory in IoT microcontrollers, and lightweight frameworks for TinyML. The book also describes TinyML techniques for real-time and environmental applications. Additional topics covered in the book include: A thorough introduction to security and privacy techniques for TinyML devices, including the implementation of novel security schemesIncisive explorations of power consumption and memory in IoT MCUs, including ultralow-power smart IoT devices with embedded TinyMLPractical discussions of TinyML research targeting microcontrollers for data extraction and synthesis Perfect for industry and academic researchers, scientists, and engineers, Tiny Machine Learning will also benefit lecturers and graduate students interested in machine learning.…

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Taschenbuch. Zustand: Neu. Neuware - Machine Learning for Wireless Communication: Principles and ApplicationsEdited by Dr. Sanjay AgalUnlock the future of connectivity where algorithms power intelligent communication systems. Machine Learning for Wireless Communication: Principles and Applications is your essential guide to the transformative synergy between machine learning and next-generation wireless technologies.Whether you're a researcher, student, or industry professional, this comprehensive volume bridges the gap between theory and practical application. Covering foundational concepts-from supervised and unsupervised learning to deep learning and reinforcement learning-it progresses into real-world applications such as 5G/6G optimization, IoT integration, edge computing, and network security.With clear explanations, illustrative case studies, and insights from seasoned educators and engineers, this book goes beyond technical depth to offer a strategic vision of how data-driven intelligence is reshaping wireless networks.Step into a world where machines not only learn but anticipate, adapt, and revolutionize how we connect.…

Buch. Zustand: Neu. Neuware - Machine Learning for Wireless Communication: Principles and ApplicationsEdited by Dr. Sanjay AgalUnlock the future of connectivity where algorithms power intelligent communication systems. Machine Learning for Wireless Communication: Principles and Applications is your essential guide to the transformative synergy between machine learning and next-generation wireless technologies.Whether you're a researcher, student, or industry professional, this comprehensive volume bridges the gap between theory and practical application. Covering foundational concepts-from supervised and unsupervised learning to deep learning and reinforcement learning-it progresses into real-world applications such as 5G/6G optimization, IoT integration, edge computing, and network security.With clear explanations, illustrative case studies, and insights from seasoned educators and engineers, this book goes beyond technical depth to offer a strategic vision of how data-driven intelligence is reshaping wireless networks.Step into a world where machines not only learn but anticipate, adapt, and revolutionize how we connect.…