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Probability in Electrical Engineering and Computer Science

An Application-Driven Course

de Jean Walrand ...

Series series Computer Science (R0)
This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, ... Leer más

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This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems,
... Leer más

Probability, Markov Chains, Queues, and Simulation

The Mathematical Basis of Performance Modeling

de William J. Stewart ...

Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a ... Leer más

$2,030 MXN

Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a
... Leer más
Math for Deep Learning

What You Need to Know to Understand Neural Networks

de Ronald T. Kneusel ...

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.You’ll work through Python examples to learn key deep learning related topics in probability, statistics, ... Leer más

$498 MXN

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning.You’ll work through Python examples to learn key deep learning related topics in probability, statistics,
... Leer más
Probability and Random Processes

With Applications to Signal Processing and Communications

de Scott Miller ...

Probability and Random Processes provides a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It includes unique chapters on narrowband random processes and simulation techniques. It also includes applications in digital communications, information theory ... Leer más

$1,448 MXN

Probability and Random Processes provides a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It includes unique chapters on narrowband random processes and simulation techniques. It also includes applications in digital communications, information theory
... Leer más
Elements of Information Theory

de Thomas M. Cover, Joy A. Thomas ...

The latest edition of this classic is updated with new problem sets and materialThe Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including ... Leer más

$1,711 MXN

The latest edition of this classic is updated with new problem sets and materialThe Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.All the essential topics in information theory are covered in detail, including
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Regularized System Identification

Learning Dynamic Models from Data

de Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, Lennart Ljung ...

Series series Engineering (R0)
This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The ... Leer más

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This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The
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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, ... Leer más

$679 MXN o gratis con 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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A First Course in Machine Learning

de Simon Rogers, Mark Girolami ...

Series series Chapman & Hall/CRC Machine Learning & Pattern Recognition
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC."—Devdatt ... Leer más

$1,072 MXN

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC."—Devdatt
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Bayesian Reasoning and Machine Learning

de David Barber ...

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to ... Leer más

$1,404 MXN

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to
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Concise Dictionary Of Mathematics

de Dr. Sudhir Dawra ...

The book is designed to provide you with dictionaries of terms in Mathematics. The terms have been arranged alphabetically for quick reference. Suitable explanations of terms that have come into public domain recently also find mention. The standard of explanation has been kept at a level of understanding expected from an average secondary and senior secondary student. Illustrations and examples, ... Leer más

$176 MXN

The book is designed to provide you with dictionaries of terms in Mathematics. The terms have been arranged alphabetically for quick reference. Suitable explanations of terms that have come into public domain recently also find mention. The standard of explanation has been kept at a level of understanding expected from an average secondary and senior secondary student. Illustrations and examples,
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Introduction to Probability Models

de Sheldon M. Ross ...

Introduction to Probability Models, Eleventh Edition is the latest version of Sheldon Ross's classic bestseller, used extensively by professionals and as the primary text for a first undergraduate course in applied probability. The book introduces the reader to elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, ... Leer más

$1,196 MXN

Introduction to Probability Models, Eleventh Edition is the latest version of Sheldon Ross's classic bestseller, used extensively by professionals and as the primary text for a first undergraduate course in applied probability. The book introduces the reader to elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering,
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Handbook of Monte Carlo Methods

de Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev ...

Series Libro 706 - Wiley Series in Probability and Statistics
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applicationsMore and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the ... Leer más

$2,398 MXN

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applicationsMore and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the
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Probability, Markov Chains, Queues, and Simulation

Math for Deep Learning

Probability and Random Processes

Elements of Information Theory

Regularized System Identification

Hands-On Mathematics for Deep Learning

A First Course in Machine Learning

Bayesian Reasoning and Machine Learning

Concise Dictionary Of Mathematics

Introduction to Probability Models

Handbook of Monte Carlo Methods