Artificial Intelligence using MATLAB 使用 MATLAB 的人工智能

www.enthutech.in

ArtificialIntelligenceusingMATLAB

TrainingContact:

GowthamRajG

Phone#:91-9597268857

gowthamraj@enthutech.in

TRAININGPROPOSAL

COURSEINFORMATION

CourseObjective

Day1-2:MATLABFundamentals

Day3:MachineLearningwithMATLAB

Day4:MachineLearningwithMATLAB-contd.andDeepLearningwithMATLABDay5:DeepLearningwithMATLAB-contd.

Prerequisites

KnowledgeofEngineeringMathematics

Schedule

Instruction9:00am-5:00pmwithscheduledbreaksandlunch.

SessionhandledbyMathworksTeam

COURSEOUTLINE

Day1-MATLABFundamentals

WorkingwiththeMATLABUserInterface(2hrs)

BecomefamiliarwiththemainfeaturesoftheMATLABintegrateddesignenvironmentanditsuserinterfaces.Getanoverviewofcoursethemes.

Readingdatafromfiles

Savingandloadingvariables

Plottingdata

Customizingplots

Exportinggraphicsforuseinotherapplications

VariablesandCommands(2.5hrs)

EnterMATLABcommands,withanemphasisoncreatingvariables,accessingandmanipulatingdatainvariables,andcreatingbasicvisualizations.CollectMATLABcommandsintoscriptsforeaseofreproductionandexperimentation.

Enteringcommands

Creatingnumericandcharactervariables

Makingandannotatingplots

Gettinghelp

Creatingandrunninglivescripts

AnalysisandVisualizationwithMatrices(2hrs)

Usematricesasmathematicalobjectsorascollectionsof(vector)data.UnderstandtheappropriateuseofMATLABsyntaxtodistinguishbetweentheseapplications.

Creatingandmanipulatingmatrices

Performingcalculationswithmatrices

Calculatingstatisticswithmatrixdata

Visualizingmatrixdata

Day2-MATLABFundamentals

TablesofData(1.5hrs)

ImportdataasaMATLABtable.Workwithdatastoredasatable.

Storingdataasatable

Operatingontables

Extractingdatafromtables

Modifyingtables

ConditionalDataSelection(2hrs)

Extractandanalyzesubsetsofdatathatsatisfygivencriteria.

Logicaloperationsandvariables

Findingandcounting

Logicalindexing

IncreasingAutomationwithProgrammingConstructs(2hrs)

Createflexiblecodethatcaninteractwiththeuser,makedecisions,andadapttodifferentsituations.

Programmingconstructs

Userinteraction

Decisionbranching

Loops

IncreasingAutomationwithFunctions(2hrs)

Increaseautomationbyencapsulatingmodulartasksasuser-definedfunctions.UnderstandhowMATLABresolvesreferencestofilesandvariables.UseMATLABdevelopmenttoolstofindandcorrectproblemswithcode.

Creatingfunctions

Callingfunctions

SettingtheMATLABpath

Debugging

Usingbreakpoints

Creatingandusingstructures

Day3-MachineLearningwithMATLAB

FindingNaturalPatternsinData(2hrs)

Useunsupervisedlearningtechniquestogroupobservationsbasedonasetofexplanatoryvariablesanddiscovernaturalpatternsinadataset.

Unsupervisedlearning

Clusteringmethods

Clusterevaluationandinterpretation

BuildingClassificationModels(3hrs)

Usesupervisedlearningtechniquestoperformpredictivemodelingforclassificationproblems.Evaluatetheaccuracyofapredictivemodel.

Supervisedlearning

Trainingandvalidation

Classificationmethods

ImprovingPredictiveModels(2hrs)

Reducethedimensionalityofadataset.Improveandsimplifymachinelearningmodels.

Crossvalidation

Hyperparameteroptimization

Featuretransformation

Featureselection

Ensemblelearning

Day4-MachineLearningwithMATLAB...-contdandDeepLearningwithMATLAB

BuildingRegressionModels(2.5hrs)

Usesupervisedlearningtechniquestoperformpredictivemodelingforcontinuousresponsevariables.

Parametricregressionmethods

Nonparametricregressionmethods

Evaluationofregressionmodels

CreatingNeuralNetworks(1hrs)

Createandtrainneuralnetworksforclusteringandpredictivemodeling.Adjustnetworkarchitecturetoimproveperformance.

ClusteringwithSelf-OrganizingMaps

Classificationwithfeed-forwardnetworks

Regressionwithfeed-forwardnetworks

TransferLearningforImageClassification(2.5hrs)

Performimageclassificationusingpretrainednetworks.Usetransferlearningtotraincustomizedclassificationnetworks.

Pretrainednetworks

Imagedatastores

Transferlearning

Networkevaluation

InterpretingNetworkBehavior(1hrs)

Gaininsightintohowanetworkisoperatingbyvisualizingimagedataasitpassesthroughthenetwork.Applythistechniquetodifferentkindsofimages.

Activations

Featureextractionformachinelearning

Day5-DeepLearningwithMATLAB

CreatingNetworks(2hrs)

Buildconvolutionalnetworksfromscratch.Understandhowinformationispassedbetweennetworklayersandhowdifferenttypesoflayerswork.

Trainingfromscratch

Neuralnetworks

Convolutionlayersandfilters

TrainingaNetwork(1hrs)

Understandhowtrainingalgorithmswork.Settrainingoptionstomonitorandcontroltraining.

Networktraining

Trainingprogressplots

Validation

ImprovingNetworkPerformance(2hrs)

Chooseandimplementmodificationstotrainingalgorithmoptions,networkarchitecture,ortrainingdatatoimprovenetworkperformance.

Trainingoptions

Directedacyclicgraphs

Augmenteddatastores

PerformingImageRegression(1hrs)

Createconvolutionalnetworksthatcanpredictcontinuousnumericresponses.

Transferlearningforregression

Evaluationmetricsforregressionnetworks

UsingDeepLearningforComputerVision(1hrs)

Trainnetworkstolocateandlabelspecificobjectswithinimages.

Imageapplicationworkflow

Objectdetection

ADDITIONALINFORMATION

AboutourServices

MathWorkstrainingisthefastestwaytomasterMATLAB,Simulink,andotherMathWorksproductsfortechnicalcomputingandModel-BasedDesign.AllcoursesaretaughtbyhighlyexperiencedMathWorksengineerswhoguideyouthroughworkflows,techni