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Python + Machine LearningIntroduction to PythonBrief historyWhy Python?Where to use?AnacondaHow to install anacondaPython BasicsThe print statementCommentsPython Data structure & Data typesString operations in PythonSimple Input & OutputOutput FormattingPython Program FlowIndentationConditional statementsifif-elseif-elif-elseNested ifLoopsforwhileNested loopsThe range statementbreak, continue and passAssertLoop examples- Star patternsList and TuplesAbout SequencesIndexing and SlicingIterating through a sequenceSequence functions, keywords and operatorsList & its methodsTuples & its methodsList ComprehensionsNested SequencesDictionaries and SetsAbout dictionariesCreating, accessing dictionariesIterating through a dictionaryDictionary methodsAbout setsCreating, accessing setsSet operationsFrozen setsFunctions & ModulesFunction – definition, callingTypes of functionsFunction parametersVariable argumentsScope of a functionFunction Documentation/ DocstringsLambda function & map, filter, reduceFunction exerciseCreate moduleStandard ModulesOOPs in PythonClass & ObjectsVariable TypeStatic variable in classCreate classesInstance methodsConstructor and destructorsInheritance and its typesPolymorphismEncapsulationScope and visibility of variablesExceptionsErrors and its typesException Handling with tryHandling multiple ExceptionsWriting own exception/ custom exceptionsRaise an ExceptionFile HandlingFile Handling modesReading filesWriting & Appending to FilesHandling file exceptionsThe with statementRegular ExpressionsSimple Character MatchesSpecial CharactersCharacter classesQuantifiersThe Dot CharacterGreedy MatchesGroupingMatching at beginning or endMatch ObjectsSubstitutingSplitting a StringData StructuresList ComprehensionsNested List comprehensionsDictionary comprehensionsIteratorsGeneratorsThe functions any and allThe with statementData CompressionCloserDecoratorWriting GUI in PythonIntroductionComponents and eventsAn example GUIThe root componentAdding a buttonEntry widgetsText widgetsCheckbuttonsRadiobuttonsListboxesFramesMenusBinding Events to widgetsThread in PythonThread life CycleThread DefinitionThread ImplementationPython MySQL Database Access IntroductionInstallationDB ConnectionCreating DB TableINSERT, READ, UPDATE, DELETE operationsCOMMIT & ROLLBACK operationHandling ErrorsINTRODUCTION TO MACHINE LEARNINGWhat is ML?Types of MLML package: scikit-learnAnacondaHow to install anacondaBasic Introduction numpy and PandasIntroduction to NumPyCreating an arrayClass and Attributes of ndarrayBasic OperationsActivity-SliceStack operationsMathematical Functions of NumPyIntroduction to PandasUnderstanding DataFrameSeriesConcatenating and appending DataFramesloc and ilocDrop columns or rowsGroupbyMap and applyData PreprocessingIntroductionDealing with missing dataHandling categorical dataEncoding class labelsOne-not encodingSplit data into training and testing setsBringing features into same scaleRegressionIntroductionSimple Linear RegressionMultiple Linear RegressionPolynomial RegressionEvaluate performance of a linear regression modelOverfitting and UnderfittingK-Nearest Neighbours (KNN)KNN theoryImplementing KNN with scikit-learnKNN parametersn_neighborsmetricHow to find nearest neighborsWriting own KNN classifier from scratchLogistic RegressionLogistic Regression theoryImplementing Logistic Regression with scikit-learnLogistic Regression ParametersMulti-class classificationMNIST digit dataset with Logistic RegressionPredictive modelling on adult income datasetSupport Vector Machine (SVM)SVM theoryImplementing SVM with scikit-learnSVM parameters:C and gammaPlot hyperplane for linear classificationDecision functionDecision Tree and Random ForestTheory behind decision treeImplementing decision tree with scikit-learnDecision tree parametersCombining multiple decision trees via Random forestHow random forest works?Na?ve Bayes ClassificationTheory Naive Bayes AlgorithmFeatures extractionCountvectorizerTF-IDFText ClassificationModel Evaluation and Parameter TuningCross validation via K-FoldTuning hyperparameters via grid searchConfusion matrixRecall and PrecisionROC and AUCClustering and Dimension ReductionK-means ClusteringElbow methodPrincipal components analysis(PCA)PCA step by stepImplementing PCA with scikit-learnLDA with scikit-learnEnsemble TechniquesIntroductionTypes of ensemble techniquesBaggingBoostingTypes of BoostingAdaBoostGradient Tree BoostingXGBoostNatural Language ProcessingInstall nltkTokenize wordsTokenizing sentencesStop words with NLTKStemming words with NLTKSpeech taggingSentiment analysis with NLTKOpenCVBasics of Computer Vision & OpenCVImage ManipulationsImage segmentationObject detectionMachine learning in Computer VisionBasics of Neural NetworksDefinition of an artificial neural networkPerceptronMinimizing cost function with Gradient descentClassifying MNIST Handwritten digits with Multilayer Perceptron ................
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