A tour of data science : learn R and Python in parallel /

Bibliographic Details
Main Author:	Zhang, Nailong (Author)
Corporate Author:	EBSCOhost
Format:	eBook
Language:	English
Published:	Abingdon, Oxon ; Boca Raton, FL : CRC Press, 2021.
Edition:	First edition.
Series:	Chapman & Hall/CRC big data series.
Subjects:	Data mining. R (Computer program language) Python (Computer program language) COMPUTERS / Programming Languages / Python COMPUTERS / Programming Languages / General COMPUTERS / Computer Graphics / Game Programming & Design Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Assumptions about the readers backgroundBook overviewIntroduction to R/Python ProgrammingCalculatorVariable and TypeFunctionsControl flowsSome built-in data structuresRevisit of variablesObject-oriented programming (OOP) in R/PythonMiscellaneousMore on R/Python ProgrammingWork with R/Python scriptsDebugging in R/PythonBenchmarkingVectorizationEmbarrassingly parallelism in R/PythonEvaluation strategySpeed up with C/C++ in R/PythonA first impression of functional programming Miscellaneousdata.table and pandasSQLGet started with data.table and pandasIndexing & selecting dataAdd/Remove/UpdateGroup byJoinRandom Variables, Distributions & Linear RegressionA refresher on distributionsInversion sampling & rejection samplingJoint distribution & copulaFit a distributionConfidence intervalHypothesis testingBasics of linear regressionRidge regressionOptimization in PracticeConvexityGradient descentRoot-findingGeneral purpose minimization tools in R/PythonLinear programmingMiscellaneousMachine Learning - A gentle introductionSupervised learningGradient boosting machineUnsupervised learningReinforcement learningDeep Q-NetworksComputational differentiationMiscellaneous