Skip to main content
Search Button
United States Kobo store Gift Cards Help

Rakuten Kobo

Wishlist

Shopping Cart

You're getting the VIP treatment!

Item(s) unavailable for purchase
Please review your cart. You can remove the unavailable item(s) now or we'll automatically remove it at Checkout.
itemsitem
itemsitem

Recommended For You

Loading...


Showing 1 - 12 of 12 results for “francis bach”
Skip side bar filters

  • Learning Theory from First Principles

    by Francis Bach ...
    Series series Adaptive Computation and Machine Learning series
    A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. . In this accessible textbook, Francis Bach presents the foundations and latest advances of learning theory for graduate students as well as researchers ... Read more

    $48.99 USD

People who read this also enjoyed

  • System Identification

    Theory for the User

    by 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 ... Read more

    $134.99 USD

  • Introduction to Machine Learning, fourth edition

    by Ethem Alpaydin ...
    Series series 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 ... Read more

    $52.99 USD

  • Machine Learning

    a Concise Introduction

    by Steven W. Knox ...
    Series Book 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 ... Read more

    $86.00 USD

  • Methods of Multivariate Analysis

    by Alvin C. Rencher, William F. Christensen ...
    Series Book 709 - Wiley Series in Probability and Statistics
    Praise for the Second Edition"This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE TransactionsFilled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data ... Read more

    $122.00 USD

  • Machine Learning

    A Constraint-Based Approach

    by Marco Gori ...
    Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic ... Read more

    $71.99 USD

  • Regularized System Identification

    Learning Dynamic Models from Data

    by 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 ... Read more

    Free

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

    by 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 ... Read more

    $120.99 USD

  • Bayesian Networks

    An Introduction

    by Timo Koski, John Noble ...
    Series Book 924 - Wiley Series in Probability and Statistics
    Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions ... Read more

    $95.00 USD

  • Data Analysis

    Edited by Gérard Govaert ...
    The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in ... Read more

    $158.00 USD

  • Kernel Methods and Machine Learning

    by S. Y. Kung ...
    Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to ... Read more

    $98.99 USD

  • Mathematical Perspectives on Neural Networks

    Edited by Paul Smolensky, Michael C. Mozer ...
    Series series Developments in Connectionist Theory Series
    Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary ... Read more

    $79.99 USD