Principles of Machine Learning

Principles of Machine Learning

Wenmin Wang

105,08 €
IVA incluido
Consulta disponibilidad
Editorial:
Springer Nature B.V.
Año de edición:
2024
Materia
Probabilidad y estadística
ISBN:
9789819753321

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)

Conducting an in-depth analysis of machine learning, this book proposes three perspectives for studying machine learning: the learning frameworks, learning paradigms, and learning tasks. With this categorization, the learning frameworks reside within the theoretical perspective, the learning paradigms pertain to the methodological perspective, and the learning tasks are situated within the problematic perspective. Throughout the book, a systematic explication of machine learning principles from these three perspectives is provided, interspersed with some examples.The book is structured into four parts, encompassing a total of fifteen chapters. The inaugural part, titled 'Perspectives,' comprises two chapters: an introductory exposition and an exploration of the conceptual foundations. The second part, 'Frameworks': subdivided into five chapters, each dedicated to the discussion of five seminal frameworks: probability, statistics, connectionism, symbolism, and behaviorism. Continuing further, the third part, 'Paradigms,' encompasses four chapters that explain the three paradigms of supervised learning, unsupervised learning, and reinforcement learning, and narrating several quasi-paradigms emerged in machine learning. Finally, the fourth part, 'Tasks': comprises four chapters, delving into the prevalent learning tasks of classification, regression, clustering, and dimensionality reduction.This book provides a multi-dimensional and systematic interpretation of machine learning, rendering it suitable as a textbook reference for senior undergraduates or graduate students pursuing studies in artificial intelligence, machine learning, data science, computer science, and related disciplines. Additionally, it serves as a valuable reference for those engaged in scientific research and technical endeavors within the realm of machine learning.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

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 €