Machine Learning Applications In Medicine – alle Bücher und CDs, Seite 3

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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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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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…

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Advances in Machine Intelligence and Computer Science Applications

Lecture Notes in Networks and Systems - Band 1882

This book belongs to a recognized series dedicated to presenting recent advances and state-of-the-art research in artificial intelligence and its applications within computer science. It aims to provide a…

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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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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…

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Signal Processing in Medicine and Biology

Signal Processing in Medicine and Biology: Applications of Deep Learning to the Health Sciences presents expanded versions of selected papers from the 2023 IEEE Signal Processing in Medicine and Biology S…

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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

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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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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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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Hugh M Cartwright
How to Use Machine Learning in Chemistry

Machine learning and artificial intelligence are hot topics across the sciences but what are they? How do machines learn and how can we apply them to problems in the chemical sciences?Written as a primer …

lieferbar ab 14.8.2026.

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Advances in Artificial Intelligence and Machine Learning

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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Subhashis Mallick
Computation, Optimization, and Machine Learning in Seismology

AGU Advanced Textbooks

A textbook applying fundamental seismology theories to the latest computational toolsThe goal of computational seismology is to digitally simulate seismic waves, create subsurface models, and match these …

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The 9th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA'25), Volume 2

Lecture Notes on Data Engineering and Communications Technologies - Band 274

This volume explores the forefront of AI innovation in building secure, sustainable, and intelligent systems. From adaptive blockchain solutions for IoT and advances in photonic quantum computing to DNS-b…

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Proceedings of the 6th International Conference on Data Science, Machine Learning and Applications- Volume 1

This book includes peer reviewed articles from the 6th International Conference on Data Science, Machine Learning and Applications, 2024, held at Tirupati on 13-14th December, in India. ICDSMLA is one of …

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The 9th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA'25), Volume 1

Lecture Notes on Data Engineering and Communications Technologies - Band 273

This volume showcases transformative AI research addressing real-world challenges across healthcare, education, law, and digital security. Highlights include explainable deep learning for berry classifica…

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Mohammad Abdul Matin, M. Rezwanul Mahmood
Machine Learning in Next Generation Multiple Access (NGMA)

Synthesis Lectures on Communications

This book equips readers with the conceptual and practical knowledge they need to put into practice the design, development, and management of the next generation multiple access / non-orthogonal multiple…

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