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Author: Lorenz Krüger
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages :
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Book Description
Author: Lorenz Krüger
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages :
Get Book Here
Book Description
Author:
Publisher:
ISBN: 9780262111188
Category : Probabilities
Languages : en
Pages : 459
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Lorenz Krüger
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 459
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Book Description
Author: Rens Bod
Publisher: A Bradford Book
ISBN: 0262025361
Category : Language Arts & Disciplines
Languages : en
Pages : 465
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Book Description
For the past forty years, linguistics has been dominated by the idea that language is categorical and linguistic competence discrete. It has become increasingly clear, however, that many levels of representation, from phonemes to sentence structure, show probabilistic properties, as does the language faculty. Probabilistic linguistics conceptualizes categories as distributions and views knowledge of language not as a minimal set of categorical constraints but as a set of gradient rules that may be characterized by a statistical distribution. Whereas categorical approaches focus on the endpoints of distributions of linguistic phenomena, probabilistic approaches focus on the gradient middle ground. Probabilistic linguistics integrates all the progress made by linguistics thus far with a probabilistic perspective. This book presents a comprehensive introduction to probabilistic approaches to linguistic inquiry. It covers the application of probabilistic techniques to phonology, morphology, semantics, syntax, language acquisition, psycholinguistics, historical linguistics, and sociolinguistics. It also includes a tutorial on elementary probability theory and probabilistic grammars.
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
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Book Description
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 and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Author: Lorenz Kruger
Publisher: MIT Press
ISBN: 0262610620
Category : Science
Languages : en
Pages : 0
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Book Description
Probability ideas are the success story common to the growth of the modern natural and social sciences. Chance, indeterminism, and statistical inference have radically and globally transformed the sciences in a "probabilistic revolution." This monumental work traces the rise, the transformation, and the diffusion of probabilistic and statistical thinking in the nineteenth and early twentieth centuries. It is less concerned with specific technical discoveries than with locating the probability revolution historically within a larger framework of ideas. There is no comparable study that treats the rise of probability and statistics in such scope and depth. The contributors - scientists, historians and philosophers from eight countries - make it possible for readers trained in many disciplines to see why the probabilistic revolution has been so complete and so successful, and how the rejection of uniform causality by quantum physics, the stochastic nature of evolutionary biology, the indeterminisms of human psychology, and the random processes of many economic activities are all manifestations of an underlying unifying concept. Volume 1 opens with provocative essays on scientific revolutions in general and the probabilistic revolution in particular by Thomas S. Kuhn, I. Bernard Cohen, and Ian Hacking. Other authors discuss the evolution of philosophical ideas about probability and their articulation and elaboration in the mathematics of the nineteenth century and describe the first applications of techniques of statistical inference during that century: Topics include the uses and abuses of official statistics by the bureaucrats of France, England, and Prussia; the use - or neglect - of statistics by nascent sociologists, demographers, and insurance actuaries; and the emergence of statistical methodologies in fields ranging from social reform to agricultural production. The emphasis in volume 2 is on the more recent scientific advances of the probabilistic approach in various natural and social sciences, from "random walks" in the stock market to random drift in natural selection, and from indeterminate events at the atomic level to unpredictable actions at the human level.
Author: Nick Chater
Publisher: OUP Oxford
ISBN: 0199216096
Category : Philosophy
Languages : en
Pages : 535
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Book Description
The Probabilistic Mind is a follow-up to the influential and highly cited Rational Models of Cognition (OUP, 1998). It brings together developmetns in understanding how, and how far, high-level cognitive processes can be understood in rational terms, and particularly using probabilistic Bayesian methods.
Author: Thomas S. Kuhn
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 199
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Book Description
Author: Gerd Gigerenzer
Publisher: Cambridge University Press
ISBN: 9780521398381
Category : History
Languages : en
Pages : 364
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Book Description
Connects the earliest applications of probability and statistics in gambling and insurance to the most recent applications in law, medicine, polling, and baseball as well as their impact on biology, physics and psychology.
