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A01=Alexander Gray
A01=Andrew J. Connolly
A01=Jacob T. VanderPlas
A01=Zeljko Ivezic
Accuracy and precision
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Astronomical survey
Astronomy
Asymptotic theory (statistics)
Author_Alexander Gray
Author_Andrew J. Connolly
Author_Jacob T. VanderPlas
Author_Zeljko Ivezic
Autoencoder
automatic-update
Bayesian
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Statistics, Data Mining, and Machine Learning in Astronomy

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the Large Synoptic Survey Telescope. Now fully updated, it presents a wealth of practical analysis problems, evaluates the techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. Python code and sample data sets are provided for all applications described in the book. The supporting data sets have been carefully selected from contemporary astronomical surveys and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, engage with the different methods, and adapt them to their own fields of interest.

An accessible textbook for students and an indispensable reference for researchers, this updated edition features new sections on deep learning methods, hierarchical Bayes modeling, and approximate Bayesian computation. The chapters have been revised throughout and the astroML code has been brought completely up to date.

  • Fully revised and expanded
  • Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets
  • Features real-world data sets from astronomical surveys
  • Uses a freely available Python codebase throughout
  • Ideal for graduate students, advanced undergraduates, and working astronomers
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A01=Alexander GrayA01=Andrew J. ConnollyA01=Jacob T. VanderPlasA01=Zeljko IvezicAccuracy and precisionAge Group_UncategorizedAlgorithmAstronomical surveyAstronomyAsymptotic theory (statistics)Author_Alexander GrayAuthor_Andrew J. ConnollyAuthor_Jacob T. VanderPlasAuthor_Zeljko IvezicAutoencoderautomatic-updateBayesianBayesian inferenceBayesian statisticsBoosting (machine learning)Category1=Non-FictionCategory=PCategory=PGCCategory=PHVBCategory=UNFCategory=UYQCentral limit theoremCluster analysisComputationConvex optimizationConvolution theoremCOP=United StatesCross-validation (statistics)Curve fittingData setDelivery_Delivery within 10-20 working daysDensity estimationDimensionEigenvalues and eigenvectorseq_computingeq_isMigrated=2eq_non-fictioneq_scienceEstimationEstimation theoryEstimatorExpectation value (quantum mechanics)Expectation–maximization algorithmFourier transformFundamental plane (elliptical galaxies)HistogramHyperparameterKernel density estimationLanguage_EnglishLikelihood functionLinear regressionLuminosity function (astronomy)Machine learningMarkov chain Monte CarloMathematical optimizationMeasurementMixture modelMonte Carlo methodNormal distributionNotation in probability and statisticsObservational astronomyObservational errorOnline machine learningOrbital resonancePA=AvailableParameter (computer programming)Price_€50 to €100Principal component analysisProbabilityProbability distributionProportionality (mathematics)PS=ActivePseudorandom number generatorRegularization (mathematics)ResultSample spaceScientific notationSloan Digital Sky SurveySN=Princeton Series in Modern Observational AstronomySobolev spacesoftlaunchSpace Telescope Science InstituteSpline (mathematics)StatisticStatistical hypothesis testingStatistical inferenceTests of general relativityTime seriesTwo-dimensional spaceVariable (mathematics)VarianceVariational method (quantum mechanics)Vectorization (mathematics)
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Product Details
  • Dimensions: 178 x 254mm
  • Publication Date: 03 Dec 2019
  • Publisher: Princeton University Press
  • Publication City/Country: US
  • Language: English
  • ISBN13: 9780691198309

About Alexander GrayAndrew J. ConnollyJacob T. VanderPlasZeljko Ivezic

Željko Ivezić is professor of astronomy at the University of Washington. Andrew J. Connolly is professor of astronomy at the University of Washington. Jacob T. VanderPlas is a software engineer at Google. Alexander Gray is vice president of AI science at IBM.

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