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Top Series in United States

Showing 1 - 12 of 12 results for “hang li”
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  • Machine Learning Methods

    by Hang Li ...
    Translated by Lu Lin, Huanqiang Zeng ...
    Series series Computer Science (R0)
    This book provides a comprehensive and systematic introduction to the principal machine learning methods, covering both supervised and unsupervised learning methods. It discusses essential methods of classification and regression in supervised learning, such as decision trees, perceptrons, support vector machines, maximum entropy models, logistic regression models and multiclass classification, as ... Read more

    $71.99 USD

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  • Practical Linear Algebra for Data Science

    From Core Concepts to Applications Using Python

    by Mike X Cohen ...
    If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world ... Read more

    $48.99 USD

  • Probability, Markov Chains, Queues, and Simulation

    The Mathematical Basis of Performance Modeling

    by William J. Stewart ...
    Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a ... Read more

    $117.39 USD

  • Pattern Recognition

    by 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 ... Read more

    $96.29 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

    $27.89 USD or Free with Kobo Plus

  • Performance Modeling and Design of Computer Systems

    Queueing Theory in Action

    by 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 ... Read more

    $86.99 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

    $71.09 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

    $14.39 USD or Free with Kobo Plus

  • Computational Complexity

    A Modern Approach

    by Sanjeev Arora, Boaz Barak ...
    This beginning graduate textbook describes both recent achievements and classical results of computational complexity theory. Requiring essentially no background apart from mathematical maturity, the book can be used as a reference for self-study for anyone interested in complexity, including physicists, mathematicians, and other scientists, as well as a textbook for a variety of courses and ... Read more

    $65.59 USD

  • 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

    $120.59 USD

  • Performance Analysis of Complex Networks and Systems

    by Piet Van Mieghem ...
    This rigorous, self-contained book describes mathematical and, in particular, stochastic and graph theoretic methods to assess the performance of complex networks and systems. It comprises three parts: the first is a review of probability theory; Part II covers the classical theory of stochastic processes (Poisson, Markov and queueing theory), which are considered to be the basic building blocks ... Read more

    $91.09 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

    $98.39 USD