Statistical Inference and Machine Learning for Big Data, Alvo

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 69870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Автор: Bradley Efron , Trevor Hastie
Название: Computer Age Statistical Inference, Student Edition
ISBN: 1108823416 ISBN-13(EAN): 9781108823418
Издательство: Cambridge Academ
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Цена: 33790.00 T
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Описание: Computing power has revolutionized the theory and practice of statistical inference. Now in paperback, and fortified with 130 class-tested exercises, this book explains modern statistical thinking from classical theories to state-of-the-art prediction algorithms. Anyone who applies statistical methods to data will value this landmark text.

Автор: Clarke, Bertrand S. (university Of Nebraska, Lincoln) Clarke, Jennifer L. (university Of Nebraska, Lincoln)
Название: Predictive statistics
ISBN: 1107028280 ISBN-13(EAN): 9781107028289
Издательство: Cambridge Academ
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Цена: 83430.00 T
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Описание: Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and `black box` settings, with computed examples.

Автор: Wasserman, Larry
Название: All of statistics: A Concise Course in Statistical Inference
ISBN: 1441923225 ISBN-13(EAN): 9781441923226
Издательство: Springer
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Цена: 53100.00 T
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Описание: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Автор: Hald Anders
Название: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713-1935
ISBN: 0387464085 ISBN-13(EAN): 9780387464084
Издательство: Springer
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Цена: 111790.00 T
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Описание: This is a history of parametric statistical inference, written by one of the most important historians of statistics of the 20th century, Anders Hald. This book can be viewed as a follow-up to his two most recent books, although this current text is much more streamlined and contains new analysis of many ideas and developments. And unlike his other books, which were encyclopedic by nature, this book can be used for a course on the topic, the only prerequisites being a basic course in probability and statistics.The book is divided into five main sections:* Binomial statistical inference;* Statistical inference by inverse probability;* The central limit theorem and linear minimum variance estimation by Laplace and Gauss;* Error theory, skew distributions, correlation, sampling distributions;* The Fisherian Revolution, 1912-1935.Throughout each of the chapters, the author provides lively biographical sketches of many of the main characters, including Laplace, Gauss, Edgeworth, Fisher, and Karl Pearson. He also examines the roles played by DeMoivre, James Bernoulli, and Lagrange, and he provides an accessible exposition of the work of R.A. Fisher.This book will be of interest to statisticians, mathematicians, undergraduate and graduate students, and historians of science.

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Автор: Concha Bielza, Pedro Larranaga
Название: Data-Driven Computational Neuroscience: Machine Learning and Statistical Models
ISBN: 110849370X ISBN-13(EAN): 9781108493703
Издательство: Cambridge Academ
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Цена: 85530.00 T
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Описание: Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This modern treatment of real world cases offers neuroscience researchers and graduate students a comprehensive, in-depth guide to statistical and machine learning methods.

Автор: Abarbanel, Henry D. I. (university Of California, San Diego)
Название: Statistical physics of data assimilation and machine learning
ISBN: 1316519635 ISBN-13(EAN): 9781316519639
Издательство: Cambridge Academ
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Цена: 58070.00 T
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Описание: The theory of data assimilation and machine learning is introduced in an accessible and pedagogical manner, with a focus on the underlying statistical physics. This modern and cross-disciplinary book is suitable for undergraduate and graduate students from science and engineering without specialized experience of statistical physics.

Автор: Ratner
Название: Statistical & Machine-Learning Data
ISBN: 1498797601 ISBN-13(EAN): 9781498797603
Издательство: Taylor&Francis
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Цена: 117390.00 T
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Описание: The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining.

Автор: Peter Buhlmann, Petros Drineas, Michael Kane, Mark van der Laan
Название: Handbook of Big Data
ISBN: 0367330733 ISBN-13(EAN): 9780367330736
Издательство: Taylor&Francis
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Цена: 73490.00 T
Наличие на складе: Невозможна поставка.
Описание: This handbook provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from statistics and computer science experts in industry and academia, the text instills a working understanding of key statistical and computing ideas that can be readily applied in research and practice.

Автор: Ratner, Bruce
Название: Statistical and Machine-Learning Data Mining:
ISBN: 0367573601 ISBN-13(EAN): 9780367573607
Издательство: Taylor&Francis
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Цена: 48990.00 T
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Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 60220.00 T
Наличие на складе: Нет в наличии.
Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.