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Showing 1 - 12 of 12 results for “zhiping lin”
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  • Analytic Learning Methods for Pattern Recognition

    by Kar-Ann Toh, Huiping Zhuang, Simon Liu, Zhiping Lin ...
    Series series Intelligent Technologies and Robotics (R0)
    This textbook is a consolidation of learning methods which comes in an analytic form. The covered learning methods include classical and advanced solutions to problems of regression, minimum classification error, maximum receiver operating characteristics, bridge regression, ensemble learning and network learning. Both the primal and dual solution forms are discussed for over-and under-determined ... Read more

    $89.99 USD

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  • 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

    $54.99 USD

  • Data Mining

    Practical Machine Learning Tools and Techniques

    by Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal, James Foulds ...
    **2026 Textbook and Academic Authors Association (TAA) Textbook Excellence "Texty" Award Winner**Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work ... Read more

    $56.99 USD

  • 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

    $77.99 USD

  • 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

    $27.99 USD or Free with Kobo Plus

  • 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

  • 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

  • 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

  • Practical Mathematics for AI and Deep Learning

    A Concise yet In-Depth Guide on Fundamentals of Computer Vision, NLP, Complex Deep Neural Networks and Machine Learning (English Edition)

    by Tamoghna Ghosh, Shravan Kumar Belagal Math ...
    To construct a system that may be referred to as having ‘Artificial Intelligence,’ it is important to develop the capacity to design algorithms capable of performing data-based automated decision-making in conditions of uncertainty. Now, to accomplish this goal, one needs to have an in-depth understanding of the more sophisticated components of linear algebra, vector calculus, probability, and ... Read more

    $14.99 USD or Free with Kobo Plus

  • 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

  • Hands-On Unsupervised Learning with Python

    Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

    by Giuseppe Bonaccorso ...
    Discover the skill-sets required to implement various approaches to Machine Learning with PythonKey FeaturesExplore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and moreBuild your own neural network models using modern Python librariesPractical examples show you how to implement different machine learning and deep learning techniquesBook DescriptionUnsupervised ... Read more

    $35.99 USD or Free with Kobo Plus

  • 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