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Data-Driven Decisions: An Introduction to Machine Learning

Technology

de Nandini K ...

Seria seria Technology
Data-Driven Decisions: An Introduction to Machine Learning provides a comprehensive and accessible introduction to the principles and applications of machine learning for students, professionals, and decision-makers. Combining theoretical foundations with practical examples, this book guides readers through key concepts such as supervised and unsupervised learning, feature engineering, model ... Citiți mai mult

174,35 lei

Data-Driven Decisions: An Introduction to Machine Learning provides a comprehensive and accessible introduction to the principles and applications of machine learning for students, professionals, and decision-makers. Combining theoretical foundations with practical examples, this book guides readers through key concepts such as supervised and unsupervised learning, feature engineering, model
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Data Analysis and Data Mining

An Introduction

de Adelchi Azzalini, Bruno Scarpa ...

An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have ... Citiți mai mult

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An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have
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Understanding Machine Learning

From Theory to Algorithms

de Shai Shalev-Shwartz, Shai Ben-David ...

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical ... Citiți mai mult

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Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical
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Introduction to Machine Learning, fourth edition

de Ethem Alpaydin ...

Seria seria Adaptive Computation and Machine Learning series
A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This ... Citiți mai mult

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A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Machine learning underlies such exciting new technologies as self-driving cars, speech recognition, and translation applications. This
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System Identification

Theory for the User

de Lennart Ljung ...

The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and ... Citiți mai mult

669,87 lei

The field's leading text, now completely updated.Modeling dynamical systems — theory, methodology, and applications.Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and
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Machine Learning

a Concise Introduction

de Steven W. Knox ...

Seria Cartea 285 - Wiley Series in Probability and Statistics
**AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONSPROSE Award Finalist 2019Association of American Publishers Award for Professional and Scholarly Excellence**Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field ... Citiți mai mult

400,03 lei

**AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONSPROSE Award Finalist 2019Association of American Publishers Award for Professional and Scholarly Excellence**Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author—an expert in the field
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Hands-On Mathematics for Deep Learning

Build a solid mathematical foundation for training efficient deep neural networks

de Jay Dawani ...

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, ... Citiți mai mult

160,83 lei sau gratuit cu Kobo Plus

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision,
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Hands-On Unsupervised Learning with Python

Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

de Giuseppe Bonaccorso ...

Discover the skill-sets required to implement various approaches to Machine Learning with PythonKey FeaturesExplore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and moreBuild your own neural network models using modern Python librariesPractical examples show you how to implement different machine learning and deep learning techniquesBook DescriptionUnsupervised ... Citiți mai mult

191,80 lei sau gratuit cu Kobo Plus

Discover the skill-sets required to implement various approaches to Machine Learning with PythonKey FeaturesExplore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and moreBuild your own neural network models using modern Python librariesPractical examples show you how to implement different machine learning and deep learning techniquesBook DescriptionUnsupervised
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Artificial Intelligence 2024 Book 2 of 2

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de Yang Yen Thaw ...

Seria Cartea 2 - AI
The book is about Artificial Intelligence for Business in Industry 4.0: Demystified by Yang Yen Thaw and includes generative AI. It is an extensive guide designed to make AI concepts accessible and applicable for business and enterprise use. It features 111 AI terms and explanations, along with a practical case study to illustrate AI implementation.The book is structured to cover a broad range of ... Citiți mai mult

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The book is about Artificial Intelligence for Business in Industry 4.0: Demystified by Yang Yen Thaw and includes generative AI. It is an extensive guide designed to make AI concepts accessible and applicable for business and enterprise use. It features 111 AI terms and explanations, along with a practical case study to illustrate AI implementation.The book is structured to cover a broad range of
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Machine Learning - A Journey To Deep Learning: With Exercises And Answers

de Andreas Miroslaus Wichert, Luis Sa-couto ...

This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning ... Citiți mai mult

598,50 lei

This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning
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Algorithms for Optimization

de Mykel J. Kochenderfer, Tim A. Wheeler ...

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will ... Citiți mai mult

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A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will
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Algorithms for Decision Making

de Mykel J. Kochenderfer, Tim A. Wheeler, Kyle H. Wray ...

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them.Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while ... Citiți mai mult

307,35 lei

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them.Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while
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Recomandate pentru dvs.

Technology Serie de Cărți electronice

Data-Driven Decisions: An Introduction to Machine Learning

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Data Analysis and Data Mining

Understanding Machine Learning

Introduction to Machine Learning, fourth edition

System Identification

Machine Learning

Hands-On Mathematics for Deep Learning

Hands-On Unsupervised Learning with Python

Artificial Intelligence 2024 Book 2 of 2

Machine Learning - A Journey To Deep Learning: With Exercises And Answers

Algorithms for Optimization

Algorithms for Decision Making