Python'seaseofuseandmulti-purposenaturehasledittobecomethechoiceoftoolformanydatascientistsandmachinelearningdeveloperstoday.Itsrichlibrariesarewidelyusedfordataanalysis,andmoreimportantly,forbuildingstate-of-the-artpredictivemodels.Thisbooktakesyouthroughanexcitingjourney,ofusingtheselibrariestoimplementeffectivestatisticalmodelsforpredictiveanalytics.You’llstartbydivingintoclassicalstatisticalanalysis,whereyouwilllearntocomputedescriptivestatisticsusingpandas.Youwilllookatsupervisedlearning,whereyouwillexploretheprinciplesofmachinelearningandtraindifferentmachinelearningmodelsfromscratch.Youwillalsoworkwithbinarypredictionmodels,suchasdataclassificationusingk-nearestneighbors,decisiontrees,andrandomforests.Thisbookalsocoversalgorithmsforregressionanalysis,suchasridgeandlassoregression,andtheirimplementationinPython.Youwillalsolearnhowneuralnetworkscanbetrainedanddeployedformoreaccuratepredictions,andwhichPythonlibrariescanbeusedtoimplementthem.Bytheendofthisbook,youwillhavealltheknowledgeyouneedtodesign,build,anddeployenterprise-gradestatisticalmodelsformachinelearningusingPythonanditsrichecosystemoflibrariesforpredictiveanalytics.