Machine Learning In Healthcare – alle Bücher, Seite 2

Rabiu Muazu Musa, Anwar P. P. Abdul Majeed
Machine Learning in Youth Badminton

SpringerBriefs in Applied Sciences and Technology

This book explores the application of machine learning techniques to model the interplay between psycho-physiological, anthropometric, and fitness variables in youth badminton athletes. The data presented…

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Debashish Das, Ali Safaa Sadiq, Seyedali Mirjalili
Optimization Algorithms in Machine Learning

Engineering Optimization: Methods and Applications

This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, g…

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Xiang-Sheng Wang, Chisheng Wang
Machine Learning in Data Processing

Forum for Interdisciplinary Mathematics

Machine learning has become a cornerstone of modern data-driven science and technology. For mathematics students and researchers, understanding the mathematical foundations behind machine learning is esse…

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Machine Learning in Water Treatment

Machine Learning in Water Treatment is a must-have for anyone interested in how artificial intelligence is transforming water treatment, offering practical insights, case studies, and a deep dive into cut…

lieferbar in mind. 4 Wochen

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Machine Learning and Deep Learning in Drug Design

Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline--fr…

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Federated Learning Applications in Healthcare

Emerging Trends in Science, Innovation and Business

"Federated Learning Applications in Healthcare: Empowering Wellness" is an ambitious and timely endeavor aimed at providing a comprehensive exploration of the intersection between federated lear…

lieferbar ab 19.1.2027.

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Namrata Manohar, Mousmi Ajay Chaurasia, Stefan Mozar, Chia-Feng Juang
Machine Learning Applications in Renewable Energy

This book presents the need for Renewable Energy Technologies (RET) in the context of providing a solution for the depletion of conventional resources, protecting the environment and enhancing the economi…

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Hasan Ali Gamal Al-Kaf, Kyo-Beum Lee
Machine Learning Integration in Power Electronics

This book provides a comprehensive guide for integrating machine learning techniques to enhance power electronic systems, with a focus on real-time applications, fault detection, and advanced control syst…

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Wilson Tsakane Mongwe, Rendani Mbuvha, Tshilidzi Marwala
Bayesian Machine Learning in Quantitative Finance

This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling problems within quantitative fi…

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Michael Koller, Oliver de Candido
Machine Learning in Safety-Critical Applications

Designed as a jumping-off point for engineers and decision-makers, this book provides a broad view of machine learning safety. It gives a validation road-map for developers and users of safety-critical sy…

lieferbar ab 28.10.2026.

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Machine Learning in Astronomy (IAU S368)

Proceedings of the International Astronomical Union Symposia and Colloquia

Today's astronomical observatories are generating more data than ever, from surveys to deep images. Machine learning methods can be a powerful tool to harness the full potential of these new observatories…

lieferbar in mind. 4 Wochen

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Roshan Srivastav, Purna C. Nayak
Applications of Machine Learning in Hydroclimatology

The Springer Series in Applied Machine Learning

Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. Th…

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Kritesh Kumar Gupta, Sudip Dey, Tanmoy Mukhopadhyay
Machine Learning in Nanoscale Materials Design

Materials Horizons: From Nature to Nanomaterials

This book provides a comprehensive overview of data-driven nano-scale characterization of materials. It covers the concept of accelerated computational characterization of nano-materials by individually a…

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Advances in Artificial Intelligence and Machine Learning

Lecture Notes in Electrical Engineering - Band 1335

This book features papers from the International Conference on Emerging Research in Computing, Information, Communication, Artificial Intelligence, and Machine Learning (ERCICAM 2024). It serves as an int…

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Advances in Artificial Intelligence and Machine Learning

Lecture Notes in Electrical Engineering - Band 1264

This book presents a collection of peer-reviewed articles from the International Conference on Advances and Applications of Artificial Intelligence and Machine Learning-ICAAAIML 2023. The book covers rese…

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Kai Li, Xin Yuan, Wei Ni
Security and Resilience in Distributed Machine Learning

Springer Series in Reliability Engineering

This book offers a comprehensive exploration of federated learning (FL), a novel approach to decentralized, privacy-preserving machine learning. This book delves into the resilience and security challenge…

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Advances in Distributed Computing and Machine Learning

Lecture Notes in Networks and Systems - Band 1956

This book is a collection of peer-reviewed best-selected research papers presented at the Seventh International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2026), organiz…

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Application of Machine Learning in Earth Sciences

Earth and Environmental Sciences Library

This book introduces the reader to applications of machine learning (ML) in Earth Sciences. In detail, it describes the basic application of machine learning algorithms and models and their potential in E…

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Md. Jalil Piran
Linear Algebra with Applications in Machine Learning

This textbook is a comprehensive, application-driven guide to mastering linear algebra from foundational principles to advanced machine learning applications. Designed for students, researchers, and profe…

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James Burridge, Nick Tosh
Inference in Statistical Modelling and Machine Learning

Statistical modelling and machine learning offer a vast toolbox of inference methods with which to model the world, discover patterns and reach beyond the data to make predictions when the truth is not ce…

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