Hands-On Markov Models with Python

HiddenMarkovModel(HMM)isastatisticalmodelbasedontheMarkovchainconcept.Hands-OnMarkovModelswithPythonhelpsyougettogripswithHMMsanddifferentinferencealgorithmsbyworkingonreal-worldproblems.Thehands-onexamplesexploredinthebookhelpyousimplifytheprocessflowinmachinelearningbyusingMarkovmodelconcepts,therebymakingitaccessibletoeveryone.Onceyou’vecoveredthebasicconceptsofMarkovchains,you’llgetinsightsintoMarkovprocesses,models,andtypeswiththehelpofpracticalexamples.Aftergraspingthesefundamentals,you’llmoveontolearningaboutthedifferentalgorithmsusedininferencesandapplyingtheminstateandparameterinference.Inadditiontothis,you’llexploretheBayesianapproachofinferenceandlearnhowtoapplyitinHMMs.Infurtherchapters,you’lldiscoverhowtouseHMMsintimeseriesanalysisandnaturallanguageprocessing(NLP)usingPython.You’llalsolearntoapplyHMMtoimageprocessingusing2D-HMMtosegmentimages.Finally,you’llunderstandhowtoapplyHMMforreinforcementlearning(RL)withthehelpofQ-Learning,andusethistechniqueforsingle-stockandmulti-stockalgorithmictrading.Bytheendofthisbook,youwillhavegraspedhowtobuildyourownMarkovandhiddenMarkovmodelsoncomplexdatasetsinordertoapplythemtoprojects.