A Tour of Data Science : Learn R and Python in Parallel (Hardcover)

Assumptions about the readers backgroundBook overview Introduction to R/Python ProgrammingCalculator Variable and TypeFunctionsControl flowsSome built-in data structuresRevisit of variablesObject-oriented programming (OOP) in R/PythonMiscellaneous More 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 Miscellaneous data.table and pandasSQLGet started with data.table and pandasIndexing & selecting dataAdd/Remove/UpdateGroup byJoin Random Variables, Distributions & Linear RegressionA refresher on distributionsInversion sampling & rejection samplingJoint distribution & copulaFit a distributionConfidence intervalHypothesis testingBasics of linear regressionRidge regression Optimization in PracticeConvexityGradient descentRoot-findingGeneral purpose minimization tools in R/PythonLinear programmingMiscellaneous Machine Learning - A gentle introductionSupervised learningGradient boosting machineUnsupervised learningReinforcement learningDeep Q-NetworksComputational differentiationMiscellaneous