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...


Top Series in Canada

Showing 1 - 12 of 12 results for “wenmin wang”
Skip side bar filters

  • Principles of Machine Learning

    The Three Perspectives

    by Wenmin Wang ...
    Series series Computer Science (R0)
    Conducting an in-depth analysis of machine learning, this book proposes three perspectives for studying machine learning: the learning frameworks, learning paradigms, and learning tasks. With this categorization, the learning frameworks reside within the theoretical perspective, the learning paradigms pertain to the methodological perspective, and the learning tasks are situated within the ... Read more

    $89.99 CAD

People who read this also enjoyed

  • Understanding Deep Learning

    by Simon J.D. Prince ...
    An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent ... Read more

    $103.99 CAD

  • Probabilistic Machine Learning

    An Introduction

    by 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 ... Read more

    $127.99 CAD

  • 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

    $95.99 CAD

  • 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

    $149.99 CAD

  • 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

  • Pathways to Machine Learning and Soft Computing

    邁向機器學習與軟計算之路（國際英文版）

    by Jyh-Horng Jeng, 鄭志宏 ...
    This book provides frequently studied and used machines together with soft computing methods such as evolutionary computation. The main topics of the machine learning cover Artificial Neural Networks (ANNs), Radial Basis Function Networks (RBFNs), Fuzzy Neural Networks (FNNs), Support Vector Machines (SVMs), and Wilcoxon Learning Machines (WLMs). The soft computing methods include Genetic ... Read more

    $8.99 CAD or Free with Kobo Plus

  • Statistical Analysis Techniques in Particle Physics

    Fits, Density Estimation and Supervised Learning

    by Ilya Narsky, Frank C. Porter ...
    Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students. ... Read more

    $140.99 CAD

  • Neural Network Methods in Natural Language Processing

    by Yoav Goldberg, Graeme Hirst ...
    Series series Synthesis Lectures on Human Language Technologies
    Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data.The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. ... Read more

    $67.99 CAD

  • Probabilistic Machine Learning

    Advanced Topics

    by Kevin P. Murphy ...
    Series series Adaptive Computation and Machine Learning series
    An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics ... Read more

    $155.99 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