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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Machine Learning Mathematics

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Machine Learning Mathematics

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Machine Learning Mathematics

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Machine Learning for Speaker Recognition

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;

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Machine Learning

Association of American Publishers Award for Professional and Scholarly Excellence Machine Learning: a Concise Introduction offers a comprehensive;

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Statistical and Machine Learning Approaches for Network Analysis

weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Mathematics and Programming for Machine Learning with R

Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R;

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Metaheuristics in Machine Learning

Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation;

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Signal Processing and Machine Learning with Applications

presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine;

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Machine Learning

This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important;

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Machine Learning

This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important;

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Quantum Machine Learning with Python

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use;

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The Mathematics of Data

science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning;

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Phase Transitions In Machine Learning

spread of statistical relational learning as well as sequence learning methodologies. In Phase Transitions in Machine Learning the authors begin;

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Understanding Machine Learning

. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to;

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Machine Learning For Financial Engineering

This volume investigates algorithmic methods based on machine learning in order to design sequential investment strategies for financial;

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Mathematics for Future Computing and Communications

For 80 years, mathematics has driven fundamental innovation in computing and communications. This timely book provides a panorama of some;

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Dynamic Fuzzy Machine Learning

Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field;

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Practical Machine Learning Cookbook

machine-learning systems Who This Book Is For This book is for analysts, statisticians, and data scientists with knowledge of fundamentals;

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Fundamentals of Machine Learning and Deep Learning in Medicine

This book provides an accessible introduction to the foundations of machine learning and deep learning in medicine for medical students;

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Developing a 21st Century Global Library for Mathematics Research

literature. Because of the precise definitions and structures within mathematics, today's information technologies and machine learning tools provide;

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Statistical Machine Learning

for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework;

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

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied;

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Advanced Computing in Industrial Mathematics

This book gathers the peer-reviewed proceedings of the 13th Annual Meeting of the Bulgarian Section of the Society for Industrial and;

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