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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Probability and Statistics for Computer Science
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Probability and Statistics for Computer Science
David Forsyth (Gebundene Ausgabe, Englisch)
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Beschreibung
This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science… features: • A treatment of random variables and expectations dealing primarily with the discrete case. • A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. • A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. • Achapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. • A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. • A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. • A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
20.02.2018
Sprache
Englisch
EAN
9783319644097
Herausgeber
Springer International Publishing
Sonderedition
Nein
Autor
David Forsyth
Seitenanzahl
367
Einbandart
Gebundene Ausgabe
Autorenporträt
David Alexander Forsyth is Fulton Watson Copp Chair in Computer Science at the University of Illinois at Urbana-Champaign, where he is a leading researcher in computer vision.
Schlagwörter
Summarizing 1D data, Boxplots, Datasets, Spatial data, Random variables, Conditional probability, Expected values, Discrete distributions, Continuous distributions, Confidence intervals, Clustering, Markov chains, regression, Significance of evidence
Thema-Inhalt
UYAM - Mathematik für Informatiker
PBT - Wahrscheinlichkeitsrechnung und Statistik
UYM - Computermodellierung und -simulation
UFM - Mathematische und statistische Software
Höhe
279 mm
Breite
21 cm
Hersteller: Palgrave Macmillan, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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