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Engineering (R0) Serie de eBooks

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  • Variational Methods for Machine Learning with Applications to Deep Networks

    de Lucas Pinheiro Cinelli, Matheus Araújo Marins, Eduardo Antônio Barros da Silva, Sérgio Lima Netto ...
    Series series Engineering (R0)
    This book provides a straightforward look at the concepts, algorithms and advantages of Bayesian Deep Learning and Deep Generative Models. Starting from the model-based approach to Machine Learning, the authors motivate Probabilistic Graphical Models and show how Bayesian inference naturally lends itself to this framework. The authors present detailed explanations of the main modern algorithms on ... Leer más

    $89.99 USD

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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 ... Leer más

    $134.99 USD

  • 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

    $110.00 USD

  • 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

    Gratis

  • 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

    $27.99 USD o gratis con Kobo Plus

  • Probabilistic Machine Learning

    An Introduction

    de Kevin P. Murphy ...
    Series series Adaptive Computation and Machine Learning series
    A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra ... Leer más

    $77.99 USD

  • 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

    $61.99 USD

  • 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

    $81.99 USD

  • 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 ... Leer más

    $120.99 USD

  • 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

    $154.00 USD

  • Parameter Estimation and Inverse Problems

    de Richard C. Aster, Brian Borchers, Clifford H. Thurber ...
    Parameter Estimation and Inverse Problems, Second Edition provides geoscience students and professionals with answers to common questions like how one can derive a physical model from a finite set of observations containing errors, and how one may determine the quality of such a model. This book takes on these fundamental and challenging problems, introducing students and professionals to the ... Leer más

    $71.09 USD

  • Bayesian Essentials with R

    de Christian P. Robert, Jean-Michel Marin ...
    Series series Mathematics and Statistics (R0)
    This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.Readers are ... Leer más

    $98.99 USD