Performance Measurement In Machine Learning – alle Bücher, Seite 2

Vadim Smolyakov
Machine Learning Algorithms in Depth

Machine Learning Algorithms in Depth dives deep into the 'how' and the 'why' of machine learning algorithms. For each category of an algorithm, you will go from math-first principles to hands-on implement…

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Machine Learning in Medical Imaging

This book constitutes the proceedings of the 15th International Workshop on Machine Learning in Medical Imaging, MLMI 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 6, 2024.The…

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Machine Learning in Astronomy (IAU S368)

IAU S368 addresses graduate students and professional astronomers who wish to leverage machine learning to unlock the potential of modern data-rich surveys and deep images, as well as archival data. Resea…

lieferbar ab 31.7.2025.

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Wilson Tsakane Mongwe, Tshilidzi Marwala, Rendani Mbuvha
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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Innovations in Machine and Deep Learning

In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and …

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Machine Learning in Modeling and Simulation

Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering…

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

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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Machine Learning Approaches in Financial Analytics

This book addresses the growing need for a comprehensive guide to the application of machine learning in financial analytics. It offers a valuable resource for both beginners and experienced professionals…

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Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machin…

lieferbar ab 1.9.2025.

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Progress in Pattern Classification and Machine Learning

Lecture Notes in Networks and Systems - Band 1557

This book highlights recent research on computer recognition systems, one of the most promising directions in artificial intelligence. Offering the comprehensive study on this field to date, it gathers 11…

lieferbar ab 13.9.2025.

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Subhashis Mallick
Computation, Optimization, and Machine Learning in Seismology

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 …

lieferbar ab 10.9.2025.

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Machine Learning Applications in Medicine and Biology

This book combines selected papers from the 2022 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB) held at Temple University. The symposium presents multidisciplinary research in the li…

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Applying Machine Learning in Science Education Research

This open access textbook offers science education researchers a hands-on guide for learning, critically examining, and integrating machine learning (ML) methods into their science education research proj…

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Generative Machine Learning Models in Medical Image Computing

Generative Machine Learning Models in Medical Image Computing" provides a comprehensive exploration of generative modeling techniques tailored to the unique demands of medical imaging. This book pres…

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NanoMind: Exploring Synergies in Nanotechnology and Machine Learning

NanoMind" serves as a captivating exploration at the crossroads of nanotechnology and machine learning, revealing the profound synergies between these two groundbreaking fields. At its core, the book…

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Machine Learning in Geohazard Risk Prediction and Assessment

Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mappingpresents an overview of the most recent developments in machine learning techniques that have resh…

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Andreas Tilevik
Multivariate Statistics and Machine Learning in R For Beginners

This book is more than just a book -- it is a full course designed as an interactive guide for beginners in multivariate analysis. Combining theoretical videos with practical examples in R, it offers read…

lieferbar ab 30.10.2025.

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Ali Othman Albaji
Machine Learning for Environmental Noise Classification in Smart Cities

We present a Machine Learning (ML) approach to monitoring and classifying noise pollution. Both methods of monitoring and classification have been proven successful. MATLAB and Python code was generated t…

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