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Artificial Intelligence (R0) eBook Series

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  • Introduction to Artificial Intelligence

    Translated by Nathanael T. Black ...
    Series series Artificial Intelligence (R0)
    This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully ... Read more

    $49.99 USD

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  • Understanding Machine Learning

    From Theory to Algorithms

    Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical ... Read more

    $61.99 USD

  • Artificial Intelligence

    A New Synthesis

    Series series The Morgan Kaufmann Series in Artificial Intelligence
    Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language ... Read more

    $73.79 USD

  • Fundamentals of Deep Learning

    Designing Next-Generation Machine Intelligence Algorithms

    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

  • Introduction to Machine Learning, fourth edition

    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

  • Essential Math for AI

    Next-Level Mathematics for Efficient and Successful AI Systems

    by 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 ... Read more

    $48.99 USD

  • Machine Learning

    a Concise Introduction

    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

  • 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

  • Probabilistic Machine Learning

    An Introduction

    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

  • Introduction to Artificial Intelligence

    Translated by Nathanael T. Black ...
    Series series Computer Science (R0)
    This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands ... Read more

    $31.99 USD

  • Pattern Recognition and Machine Learning

    by Y. Anzai ...
    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the ... Read more

    $65.69 USD

  • Hands-On Unsupervised Learning with Python

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

    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