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Showing 1 - 12 of 12 results for “uwe ligges”
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  • Foundations of Statistical Algorithms

    With References to R Packages

    by Claus Weihs, Olaf Mersmann, Uwe Ligges ...
    Series series Chapman & Hall/CRC Computer Science & Data Analysis
    A new and refreshingly different approach to presenting the foundations of statistical algorithms, Foundations of Statistical Algorithms: With References to R Packages reviews the historical development of basic algorithms to illuminate the evolution of today's more powerful statistical algorithms. It emphasizes recurring themes in all statistical ... Read more

    $89.99 USD

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  • 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

    $110.19 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

  • Fundamentals of Deep Learning

    Designing Next-Generation Machine Intelligence Algorithms

    by Nithin Buduma, Nikhil Buduma, Joe Papa ...
    We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.The updated second edition ... Read more

    $48.99 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

  • 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

  • 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

  • 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

    $120.59 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

  • Algorithms for Optimization

    by Mykel J. Kochenderfer, Tim A. Wheeler ...
    A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will ... Read more

    $58.99 USD