Skip to main content
Search Button
Canada 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...


Engineering (R0) eBook Series

Showing 1 - 12 of 12 results
Skip side bar filters

  • Data-Driven, Nonparametric, Adaptive Control Theory

    by Andrew J. Kurdila, Andrea L'Afflitto, John A. Burns ...
    Series series Engineering (R0)
    Data-Driven, Nonparametric, Adaptive Control Theory introduces a novel approach to the control of deterministic, nonlinear ordinary differential equations affected by uncertainties. The methods proposed enforce satisfactory trajectory tracking despite functional uncertainties in the plant model. The book employs the properties of reproducing kernel Hilbert (native) spaces to characterize both the ... Read more

    $205.99 CAD

People who read this also enjoyed

  • Essential Math for AI

    Next-Level Mathematics for Efficient and Successful AI Systems

    by Hala Nelson ...
    Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.Engineers, data scientists, and students alike will examine ... Read more

    $67.99 CAD

  • Understanding Machine Learning

    From Theory to Algorithms

    by 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 ... Read more

    $68.99 CAD

  • Hands-On Mathematics for Deep Learning

    Build a solid mathematical foundation for training efficient deep neural networks

    by 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, ... Read more

    $37.99 CAD or Free with Kobo Plus

  • 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

    $70.39 CAD

  • 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

    $151.99 CAD

  • Mathematical Perspectives on Neural Networks

    Edited by Paul Smolensky, Michael C. Mozer, David E. Rumelhart ...
    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

    $119.99 CAD

  • Pattern Recognition and Machine Learning

    by Y. Anzai ...
    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the ... Read more

    $64.79 CAD

  • 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

    $83.99 CAD

  • Bayesian Reasoning and Machine Learning

    by 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 ... Read more

    $91.99 CAD

  • Monte-Carlo Methods and Stochastic Processes

    From Linear to Non-Linear

    by Emmanuel Gobet ...
    Developed from the author’s course at the Ecole Polytechnique, Monte-Carlo Methods and Stochastic Processes: From Linear to Non-Linear focuses on the simulation of stochastic processes in continuous time and their link with partial differential equations (PDEs). It covers linear and nonlinear problems in biology, finance, geophysics, mechanics, chemistry, and other application areas. The text also ... Read more

    $102.99 CAD