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1-12 sur 12 résultats pour « nong ye »
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  • Developing Windows-Based and Web-Enabled Information Systems

    par Nong Ye, Teresa Wu ...
    Collections series Data-Enabled Engineering
    Many professionals and students in engineering, science, business, and other application fields need to develop Windows-based and web-enabled information systems to store and use data for decision support, without help from professional programmers. However, few books are available to train professionals and students who are not professional progra ... En savoir plus

    $130.99 CAD

  • Data Mining

    Theories, Algorithms, and Examples

    par Nong Ye ...
    Collections series Human Factors and Ergonomics
    New technologies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various dat ... En savoir plus

    $130.99 CAD

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  • Essential Math for AI

    Next-Level Mathematics for Efficient and Successful AI Systems

    par 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 ... En savoir plus

    $67.99 CAD

  • Probabilistic Machine Learning

    An Introduction

    par Kevin P. Murphy ...
    Collections 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 ... En savoir plus

    $127.99 CAD

  • Pattern Recognition

    par Konstantinos Koutroumbas, Sergios Theodoridis ...
    This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods ... En savoir plus

    $95.99 CAD

  • Hands-On Mathematics for Deep Learning

    Build a solid mathematical foundation for training efficient deep neural networks

    par 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, ... En savoir plus

    $37.99 CAD ou Gratuit avec Kobo Plus

  • Introduction to Machine Learning, fourth edition

    par Ethem Alpaydin ...
    Collections 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 ... En savoir plus

    $95.99 CAD

  • System Identification

    Theory for the User

    par 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 ... En savoir plus

    $149.99 CAD

  • Machine Learning

    a Concise Introduction

    par Steven W. Knox ...
    Collections Livre 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 ... En savoir plus

    $119.99 CAD

  • Performance Modeling and Design of Computer Systems

    Queueing Theory in Action

    par Mor Harchol-Balter ...
    Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly ... En savoir plus

    $97.99 CAD

  • 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)

    par 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 ... En savoir plus

    $21.99 CAD ou Gratuit avec Kobo Plus

  • Mathematics for Machine Learning: A Deep Dive into Algorithms

    par NIBEDITA Sahu ...
    Mathematics for Machine Learning is a comprehensive guide that bridges the gap between mathematical theory and practical applications in the dynamic world of machine learning. Whether you're a data science enthusiast, a budding machine learning engineer, or a seasoned practitioner, this book equips you with the essential mathematical foundations that power cutting-edge algorithms and data-driven ... En savoir plus

    $23.99 CAD ou Gratuit avec Kobo Plus