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Density Ratio Estimation in Machine Learning

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications;

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Density Ratio Estimation in Machine Learning

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications;

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Machine Learning Theoretical Foundations and Practical Applications

algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory;

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Mathematical Theories of Machine Learning - Theory and Applications

This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing;

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Linear Algebra and Optimization with Applications to Machine Learning - Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning

mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary;

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Machine Learning in Finance

covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective;

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Machine Learning in Finance

covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective;

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Machine Learning Guide for Oil and Gas Using Python

critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil;

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Machine Learning in Healthcare

covers fundamental concepts including mathematical requisites and traditional machine-learning framework followed by advanced machine-learning;

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Machine Learning for Robotics Applications

in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both;

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Brain and Nature-Inspired Learning, Computation and Recognition

recognitionDescribes the biological mechanisms, mathematical analyses and scientific principles behind brain and nature-inspired learning;

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Introduction to Online Convex Optimization, second edition

presents a robust machine learning approach that contains elements of mathematical optimization, game theory, and learning theory: an optimization;

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Statistical Machine Learning

provides students, engineers, and scientists with tools from mathematical statistics and nonlinear optimization theory to become experts in the;

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Machine Learning and the Internet of Medical Things in Healthcare

healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and;

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Cognitive Informatics, Computer Modelling, and Cognitive Science

, including coverage of cognitive knowledge base, information theory, cognitive machine learning and intelligence;

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Machine Learning in Industry

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep;

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Learning Control

Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also;

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Quantitative Graph Theory

The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications;

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Quantitative Graph Theory

The first book devoted exclusively to quantitative graph theory, Quantitative Graph Theory: Mathematical Foundations and Applications;

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning;

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Introduction to Machine Learning with Applications in Information Security

wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and;

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Theories of Human Learning

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and;

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Theories of Human Learning

Both a serious academic text and an intriguing story, this seventh edition reflects a significant update in research, theory, and;

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Machine Learning

reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how;

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Handbook Of Machine Learning - Volume 1

This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and;

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Proceedings of International Conference on Big Data Machine Learning and Applic

Applications (BigDML 2019). It focuses on both theory and applications in the broad areas of big data and machine learning. It brings together the;

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Big Data Analytics for Cyber-Physical Systems

, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the;

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