Machinelearningisappliedeverywhere,frombusinesstoresearchandacademia,whilescikit-learnisaversatilelibrarythatispopularamongmachinelearningpractitioners.Thisbookservesasapracticalguideforanyonelookingtoprovidehands-onmachinelearningsolutionswithscikit-learnandPythontoolkits.Thebookbeginswithanexplanationofmachinelearningconceptsandfundamentals,andstrikesabalancebetweentheoreticalconceptsandtheirapplications.Eachchaptercoversadifferentsetofalgorithms,andshowsyouhowtousethemtosolvereal-lifeproblems.You’llalsolearnaboutvariouskeysupervisedandunsupervisedmachinelearningalgorithmsusingpracticalexamples.Whetheritisaninstance-basedlearningalgorithm,Bayesianestimation,adeepneuralnetwork,atree-basedensemble,orarecommendationsystem,you’llgainathoroughunderstandingofitstheoryandlearnwhentoapplyit.Asyouadvance,you’lllearnhowtodealwithunlabeleddataandwhentousedifferentclusteringandanomalydetectionalgorithms.Bytheendofthismachinelearningbook,you’llhavelearnedhowtotakeadata-drivenapproachtoprovideend-to-endmachinelearningsolutions.You’llalsohavediscoveredhowtoformulatetheproblemathand,preparerequireddata,andevaluateanddeploymodelsinproduction.