Python：Advanced Guide to Artificial Intelligence
ThisLearningPathisyourcompleteguidetoquicklygettingtogripswithpopularmachinelearningalgorithms.You'llbeintroducedtothemostwidelyusedalgorithmsinsupervised,unsupervised,andsemi-supervisedmachinelearning,andlearnhowtousetheminthebestpossiblemanner.RangingfromBayesianmodelstotheMCMCalgorithmtoHiddenMarkovmodels,thisLearningPathwillteachyouhowtoextractfeaturesfromyourdatasetandperformdimensionalityreductionbymakinguseofPython-basedlibraries.You'llbringtheuseofTensorFlowandKerastobuilddeeplearningmodels,usingconceptssuchastransferlearning,generativeadversarialnetworks,anddeepreinforcementlearning.Next,you'lllearntheadvancedfeaturesofTensorFlow1.x,suchasdistributedTensorFlowwithTFclusters,deployproductionmodelswithTensorFlowServing.You'llimplementdifferenttechniquesrelatedtoobjectclassification,objectdetection,imagesegmentation,andmore.BytheendofthisLearningPath,you'llhaveobtainedin-depthknowledgeofTensorFlow,makingyouthego-topersonforsolvingartificialintelligenceproblemsThisLearningPathincludescontentfromthefollowingPacktproducts:MasteringMachineLearningAlgorithmsbyGiuseppeBonaccorso.MasteringTensorFlow1.xbyArmandoFandango.DeepLearningforComputerVisionbyRajalingappaaShanmugamani.
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