Inicio > Matemáticas y ciencia > Matemáticas > Probabilidad y estadística > Artificial Intelligence
Artificial Intelligence

Artificial Intelligence

Charu C. Aggarwal

50,33 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2021
Materia
Probabilidad y estadística
ISBN:
9783030723583
50,33 €
IVA incluido
Disponible

Selecciona una librería:

  • Librería Samer Atenea
  • Librería Aciertas (Toledo)
  • Kálamo Books
  • Librería Perelló (Valencia)
  • Librería Elías (Asturias)
  • Donde los libros
  • Librería Kolima (Madrid)
  • Librería Proteo (Málaga)
Sobre IBD

This textbook covers the broader field of artificial intelligence.   The chapters for this textbook span within three categories:Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5.Inductive Learning Methods:  These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters~6 through 11. Integrating Reasoning and Learning:  Chapters~11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence.The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.

Artículos relacionados

  • ENGINEERING UNCERTAINTY AND RISK ANALYSIS
    Sergio E. Serrano
    An integrated coverage of probability, statistics, Monte Carlo simulation, inferential statistics, design of experiments, systems reliability, fitting random data to models, analysis of variance, stochastic processes, and stochastic differential equations for engineers and scientists. The author for first time presents an introduction to the broad field of applied engineering u...
    Disponible

    134,56 €

  • UNDERSTANDING AND CALCULATING THE ODDS
    Catalin Barboianu
    Man’s daily life is full of decisional situations. Whether we have math skills or not, we frequently estimate and compare probabilities, sometimes without realizing it, especially when making decisions. But probabilities are not just simple numbers attached objectively or subjectively to events, as they perhaps look, and their calculus and usage is highly predisposed to qualita...
    Disponible

    31,61 €

  • Random Graphs and Complex Networks
    Remco van der Hofstad
    ...
  • Introduction to Malliavin Calculus
    David Nualart / Eulalia Nualart
    ...
    Disponible

    60,35 €

  • Probability, Markov Chains, Queues, and Simulation
    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 process...
  • SPSS for you
    A. Rajathi / P. Chandran
    In an era where statistical analysis underpins breakthroughs across all fields, the importance of mastering statistical software cannot be overstated. 'SPSS for you' emerges as a pivotal resource for anyone keen to navigate the complexities of statistical analysis with ease and precision. Drawing from over 25 years of teaching experience, practical guidance in statistical analy...
    Disponible

    29,30 €

Otros libros del autor

  • Probability and Statistics for Machine Learning
    Charu C. Aggarwal
    This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its...
  • Neural Networks and Deep Learning
    Charu C. Aggarwal
    This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks wor...
  • Neural Networks and Deep Learning
    Charu C. Aggarwal
    This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks wor...
    Disponible

    50,49 €

  • Machine Learning for Text
    Charu C. Aggarwal
    This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7...
    Disponible

    83,40 €

  • Artificial Intelligence
    Charu C. Aggarwal
    This textbook covers the broader field of artificial intelligence.   The chapters for this textbook span within three categories:Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters...
    Disponible

    92,50 €

  • Machine Learning for Text
    Charu C. Aggarwal
    This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7...