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AbouttheTutorial

Artificialintelligenceistheintelligencedemonstratedbymachines,incontrasttotheintelligencedisplayedbyhumans.

ThistutorialcoversthebasicconceptsofvariousfieldsofartificialintelligencelikeArtificialNeuralNetworks,NaturalLanguageProcessing,MachineLearning,DeepLearning,Geneticalgorithmsetc.,anditsimplementationinPython.

Audience

Thistutorialwillbeusefulforgraduates,postgraduates,andresearchstudentswhoeitherhaveaninterestinthissubjectorhavethissubjectasapartoftheircurriculum.Thereadercanbeabeginneroranadvancedlearner.

Prerequisites

WeassumethatthereaderhasbasicknowledgeaboutArtificialIntelligenceandPythonprogramming.He/sheshouldbeawareaboutbasicterminologiesusedinAIalongwithsomeusefulpythonpackageslikenltk,OpenCV,pandas,OpenAIGym,etc.

Copyright&Disclaimer

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TableofContents

TOC\o"1-2"\h\z\u

AbouttheTutorial i

Audience i

Prerequisites i

Copyright&Disclaimer i

TableofContents ii

AIwithPython–PrimerConcepts 1

BasicConceptofArtificialIntelligence(AI) 1

TheNecessityofLearningAI 1

WhatisIntelligence? 2

WhatisIntelligenceComposedOf? 3

Learning−l 4

What’sInvolvedinAI 6

ApplicationofAI 6

CognitiveModeling:SimulatingHumanThinkingProcedure 7

Agent&Environment 8

AIwithPython–GettingStarted 9

WhyPythonforAI 9

FeaturesofPython 9

InstallingPython 10

SettingupPATH 11

RunningPython 12

ScriptfromtheCommand-line 13

IntegratedDevelopmentEnvironment 13

AIwithPython–MachineLearning 15

TypesofMachineLearning(ML) 15

MostCommonMachineLearningAlgorithms 16

AIwithPython–DataPreparation 20

PreprocessingtheData 20

TechniquesforDataPreprocessing 21

LabelingtheData 23

AIwithPython–SupervisedLearning:Classification 26

StepsforBuildingaClassifierinPython 26

BuildingClassifierinPython 29

LogisticRegression 34

DecisionTreeClassifier 37

RandomForestClassifier 39

Performanceofaclassifier 40

ClassImbalanceProblem 42

EnsembleTechniques 43

AIwithPython–SupervisedLearning:Regression 44

BuildingRegressorsinPython 44

AIwithPython–LogicProgramming 49

HowtoSolveProblemswithLogicProgramming 49

InstallingUsefulPackages 50

ExamplesofLogicProgramming 50

CheckingforPrimeNumbers 51

SolvingPuzzles 52

AIwithPython–UnsupervisedLearning:Clustering 55

WhatisClustering? 55

AlgorithmsforClusteringtheData 55

MeasuringtheClusteringPerformance 61

CalculatingSilhouetteScore 61

FindingNearestNeighbors 63

K-NearestNeighborsClassifier 65

AIwithPython–NaturalLanguageProcessing 69

ComponentsofNLP 69

DifficultiesinNLU 69

NLPTerminology 70

StepsinNLP 70

AIwithPython–NLTKpackage 72

ImportingNLTK 72

DownloadingNLTK’sData 72

InstallingOtherNecessaryPackages 73

ConceptofTokenization,Stemming,andLemmatization 73

Chunking:DividingDataintoChunks 75

Typesofchunking 76

BagofWord(BoW)Model 77

ConceptoftheStatistics 78

BuildingaBagofWordsModelinNLTK 79

SolvingProblems 79

TopicModeling:IdentifyingPatternsinTextData 84

AlgorithmsforTopicModeling 84

AIwithPython–AnalyzingTimeSeriesData 86

Introduction 86

InstallingUsefulPackages 86

Pandas:Handling,SlicingandExtractingStatisticfromTimeSeriesData 87

ExtractingStatisticfromTimeSeriesData 91

AnalyzingSequentialDatabyHiddenMarkovModel(HMM) 95

Example:AnalysisofStockMarketdata 96

AIwithPython–SpeechRecognition 99

BuildingaSpeechRecognizer 99

VisualizingAudioSignals-ReadingfromaFileandWorkingonit 100

CharacterizingtheAudioSignal:TransformingtoFrequencyDomain 102

GeneratingMonotoneAudioSignal 104

FeatureExtractionfromSpeech 106

RecognitionofSpokenWords 108

AIwithPython–HeuristicSearch 111

ConceptofHeuristicSearchinAI 111

DifferencebetweenUninformedandInformedSearch 111

RealWorldProblemSolvedbyConstraintSatisfaction 112

AIwithPython–Gaming 115

SearchAlgorithms 115

CombinationalSearch 115

MinimaxAlgorithm 115

Alpha-BetaPruning 116

NegamaxAlgorithm 116

BuildingBotstoPlayGames 116

ABottoPlayLastCoinStanding 116

ABottoPlayTicTacToe 119

AIwithPython–NeuralNetworks 122

WhatisArtificialNeuralNetworks(ANN) 122

InstallingUsefulPackages 122

BuildingNeuralNetworks 122

PerceptronbasedClassifier 123

Single-LayerNeuralNetworks 124

Multi-LayerNeuralNetworks 127

AIwithPython–ReinforcementLearning 131

BasicsofReinforcementLearning 131

BuildingBlocks:EnvironmentandAgent 131

ConstructinganEnvironmentwithPython 133

ConstructingalearningagentwithPython 134

AIwithPython–GeneticAlgorithms 135

WhatareGeneticAlgorithms? 135

HowtoUseGAforOptimizationProblems? 135

InstallingNecessaryPackages 136

ImplementingSolutionsusingGeneticAlgorithms 136

AIwithPython–ComputerVision 142

ComputerVision 142

ComputerVisionVsImageProcessing 142

InstallingUsefulPackages 143

Reading,WritingandDisplayinganImage 144

ColorSpaceConversion 145

EdgeDetection 147

FaceDetection 148

EyeDetection 149

AIwithPython–DeepLearning 151

MachineLearningv/sDeepLearning 151

ConvolutionalNeuralNetwork(CNN) 151

InstallingUsefulPythonPackages 152

BuildingLinearRegressorusingANN 153

ImageClassifier:AnApplicationofDeepLearning 154

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AIwithPython

AIwithPython–PrimerConcepts

Sincetheinventionofcomputersormachines,theircapabilitytoperformvarioustaskshasexperiencedanexponentialgrowth.Humanshavedevelopedthepowerofcomputersystemsintermsoftheirdiverseworkingdomains,theirincreasingspeed,andreducingsizewithrespecttotime.

AbranchofComputerSciencenamedArtificialIntelligencepursuescreatingthecomputersormachinesasintelligentashumanbeings.

BasicConceptofArtificialIntelligence(AI)

AccordingtothefatherofArtificialIntelligence,JohnMcCarthy,itis“Thescienceandengineeringofmakingintelligentmachines,especiallyintelligentcomputerprograms”.

ArtificialIntelligenceisawayofmakingacomputer,acomputer-controlledrobot,orasoftwarethinkintelligently,inthesimilarmannertheintelligenthumansthink.AIisaccomplishedbystudyinghowhumanbrainthinksandhowhumanslearn,decide,andworkwhiletryingtosolveaproblem,andthenusingtheoutcomesofthisstudyasabasisofdevelopingintelligentsoftwareandsystems.

Whileexploitingthepowerofthecomputersystems,thecuriosityofhuman,leadhimtowonder,“Canamachinethinkandbehavelikehumansdo?”

Thus,thedevelopmentofAIstartedwiththeintentionofcreatingsimilarintelligenceinmachinesthatwefindandregardhighinhumans.

TheNecessityofLearningAI

AsweknowthatAIpursuescreatingthemachinesasintelligentashumanbeings.TherearenumerousreasonsforustostudyAI.Thereasonsareasfollows:

AIcanlearnthroughdata

Inourdailylife,wedealwithhugeamountofdataandhumanbraincannotkeeptrackofsomuchdata.Thatiswhyweneedtoautomatethethings.Fordoingautomation,weneedtostudyAIbecauseitcanlearnfromdataandcandotherepetitivetaskswithaccuracyandwithouttiredness.

AIcanteachitself

Itisverynecessarythatasystemshouldteachitselfbecausethedataitselfkeepschangingandtheknowledgewhichisderivedfromsuchdatamustbeupdatedconstantly.WecanuseAItofulfillthispurposebecauseanAIenabledsystemcanteachitself.

AIcanrespondinrealtime

Artificialintelligencewiththehelpofneuralnetworkscananalyzethedatamoredeeply.Duetothiscapability,AIcanthinkandrespondtothesituationswhicharebasedontheconditionsinrealtime.

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AIachievesaccuracy

Withthehelpofdeepneuralnetworks,AIcanachievetremendousaccuracy.AIhelpsinthefieldofmedicinetodiagnosediseasessuchascancerfromtheMRIsofpatients.

AIcanorganizedatatogetmostoutofit

Thedataisanintellectualpropertyforthesystemswhichareusingself-learningalgorithms.WeneedAItoindexandorganizethedatainawaythatitalwaysgivesthebestresults.

UnderstandingIntelligence

WithAI,smartsystemscanbebuilt.Weneedtounderstandtheconceptofintelligencesothatourbraincanconstructanotherintelligencesystemlikeitself.

WhatisIntelligence?

Theabilityofasystemtocalculate,reason,perceiverelationshipsandanalogies,learnfromexperience,storeandretrieveinformationfrommemory,solveproblems,comprehendcomplexideas,usenaturallanguagefluently,classify,generalize,andadaptnewsituations.

TypesofIntelligence

AsdescribedbyHowardGardner,anAmericandevelopmentalpsychologist,Intelligencecomesinmultifold:

Intelligence

Description

Example

Linguisticintelligence

Theabilitytospeak,recognize,andusemechanismsofphonology(speechsounds),syntax(grammar),andsemantics(meaning).

Narrators,Orators

Musicalintelligence

Theabilitytocreate,communicatewith,andunderstandmeaningsmadeofsound,understandingofpitch,rhythm.

Musicians,Singers,Composers

Logical-mathematicalintelligence

Theabilitytouseandunderstandrelationshipsintheabsenceofactionorobjects.Itisalsotheabilitytounderstandcomplexandabstractideas.

Mathematicians,Scientists

Spatialintelligence

Theabilitytoperceivevisualorspatialinformation,changeit,andre-createvisualimageswithoutreferencetotheobjects,construct3D

Map readers,Astronauts,Physicists

images,andtomoveandrotatethem.

Bodily-Kinestheticintelligence

Theabilitytousecompleteorpartofthebodytosolveproblemsorfashionproducts,controloverfineandcoarsemotorskills,andmanipulatetheobjects.

Players,Dancers

Intra-personalintelligence

Theabilitytodistinguishamongone’sownfeelings,intentions,andmotivations.

GautamBuddhha

Interpersonalintelligence

Theabilitytorecognizeandmakedistinctionsamongotherpeople’sfeelings,beliefs,andintentions.

MassCommunicators,Interviewers

Youcansayamachineorasystemisartificiallyintelligentwhenitisequippedwithatleastoneorallintelligencesinit.

WhatisIntelligenceComposedOf?

Theintelligenceisintangible.Itiscomposedof−

Reasoning

Learning

ProblemSolving

Perception

LinguisticIntelligence

Letusgothroughallthecomponentsbriefly−

Reasoning

Itisthesetofprocessesthatenableustoprovidebasisforjudgement,makingdecisions,andprediction.Therearebroadlytwotypes−

InductiveReasoning

DeductiveReasoning

Itconductsspecificobservationstomakesbroadgeneralstatements.

Itstartswithageneralstatement and

examines thepossibilitiestoreachaspecific, logicalconclusion.

Evenifallofthepremisesaretrueinastatement,inductivereasoningallowsfortheconclusiontobefalse.

Ifsomethingistrueofaclassofthingsingeneral,itisalsotrueforallmembersofthatclass.

Example−"Nitaisateacher.Nitaisstudious.Therefore,Allteachersarestudious."

Example−"Allwomenofageabove60yearsaregrandmothers.Shaliniis65years.Therefore,Shaliniisagrandmother."

Learning−l

Theabilityoflearningispossessedbyhumans,particularspeciesofanimals,andAI-enabledsystems.Learningiscategorizedasfollows−

AuditoryLearning

Itislearningbylisteningandhearing.Forexample,studentslisteningtorecordedaudiolectures.

EpisodicLearning

Tolearnbyrememberingsequencesofeventsthatonehaswitnessedorexperienced.Thisislinearandorderly.

MotorLearning

Itislearningbyprecisemovementofmuscles.Forexample,pickingobjects,writing,etc.

ObservationalLearning

Tolearnbywatchingandimitatingothers.Forexample,childtriestolearnbymimickingherparent.

PerceptualLearning

Itislearningtorecognizestimulithatonehasseenbefore.Forexample,identifyingandclassifyingobjectsandsituations.

RelationalLearning

Itinvolveslearningtodifferentiateamongvariousstimulionthebasisofrelationalproperties,ratherthanabsoluteproperties.ForExample,Adding‘littleless’saltatthetimeofcookingpotatoesthatcameupsaltylasttime,whencookedwithaddingsayatablespoonofsalt.

SpatialLearning−Itislearningthroughvisualstimulisuchasimages,colors,maps,etc.Forexample,Apersoncancreateroadmapinmindbeforeactuallyfollowingtheroad.

Stimulus-ResponseLearning−Itislearningtoperformaparticularbehaviorwhenacertainstimulusispresent.Forexample,adograisesitsearonhearingdoorbell.

ProblemSolving

Itistheprocessinwhichoneperceivesandtriestoarriveatadesiredsolutionfromapresentsituationbytakingsomepath,whichisblockedbyknownorunknownhurdles.

Problemsolvingalsoincludesdecisionmaking,whichistheprocessofselectingthebestsuitablealternativeoutofmultiplealternativestoreachthedesiredgoal.

Perception

Itistheprocessofacquiring,interpreting,selecting,andorganizingsensoryinformation.

Perceptionpresumessensing.Inhumans,perceptionisaidedbysensoryorgans.InthedomainofAI,perceptionmechanismputsthedataacquiredbythesensorstogetherinameaningfulmanner.

LinguisticIntelligence

Itisone’sabilitytouse,comprehend,speak,andwritetheverbalandwrittenlanguage.Itisimportantininterpersonalcommunication.

What’sInvolvedinAI

Artificialintelligenceisavastareaofstudy.Thisfieldofstudyhelpsinfindingsolutionstorealworldproblems.

LetusnowseethedifferentfieldsofstudywithinAI:

MachineLearning

ItisoneofthemostpopularfieldsofAI.Thebasicconceptofthisfiledistomakethemachinelearningfromdataasthehumanbeingscanlearnfromhis/herexperience.Itcontainslearningmodelsonthebasisofwhichthepredictionscanbemadeonunknowndata.

Logic

Itisanotherimportantfieldofstudyinwhichmathematicallogicisusedtoexecutethecomputerprograms.Itcontainsrulesandfactstoperformpatternmatching,semanticanalysis,etc.

Searching

Thisfieldofstudyisbasicallyusedingameslikechess,tic-tac-toe.Searchalgorithmsgivetheoptimalsolutionaftersearchingthewholesearchspace.

Artificialneuralnetworks

Thisisanetworkofefficientcomputingsystemsthecentralthemeofwhichisborrowedfromtheanalogyofbiologicalneuralnetworks.ANNcanbeusedinrobotics,speechrecognition,speechprocessing,etc.

GeneticAlgorithm

Geneticalgorithmshelpinsolvingproblemswiththeassistanceofmorethanoneprogram.Theresultwouldbebasedonselectingthefittest.

KnowledgeRepresentation

Itisthefieldofstudywiththehelpofwhichwecanrepresentthefactsinawaythemachinethatisunderstandabletothemachine.Themoreefficientlyknowledgeisrepresented;themoresystemwouldbeintelligent.

ApplicationofAI

Inthissection,wewillseethedifferentfieldssupportedbyAI:

Gaming

AIplayscrucialroleinstrategicgamessuchaschess,poker,tic-tac-toe,etc.,wheremachinecanthinkoflargenumberofpossiblepositionsbasedonheuristicknowledge.

NaturalLanguageProcessing

Itispossibletointeractwiththecomputerthatunderstandsnaturallanguagespokenbyhumans.

ExpertSystems

Therearesomeapplicationswhichintegratemachine,software,andspecialinformationtoimpartreasoningandadvising.Theyprovideexplanationandadvicetotheusers.

VisionSystems

Thesesystemsunderstand,interpret,andcomprehendvisualinputonthecomputer.Forexample,

Aspyingaeroplanetakesphotographs,whichareusedtofigureoutspatialinformationormapoftheareas.

Doctorsuseclinicalexpertsystemtodiagnosethepatient.

Policeusecomputersoftwarethatcanrecognizethefaceofcriminalwiththestoredportraitmadebyforensicartist.

SpeechRecognition

Someintelligentsystemsarecapableofhearingandcomprehendingthelanguageintermsofsentencesandtheirmeaningswhileahumantalkstoit.Itcanhandledifferentaccents,slangwords,noiseinthebackground,changeinhuman’snoiseduetocold,etc.

HandwritingRecognition

Thehandwritingrecognitionsoftwarereadsthetextwrittenonpaperbyapenoronscreenbyastylus.Itcanrecognizetheshapesofthelettersandconvertitintoeditabletext.

IntelligentRobots

Robotsareabletoperformthetasksgivenbyahuman.Theyhavesensorstodetectphysicaldatafromtherealworldsuchaslight,heat,temperature,movement,sound,bump,andpressure.Theyhaveefficientprocessors,multiplesensorsandhugememory,toexhibitintelligence.Inaddition,theyarecapableoflearningfromtheirmistakesandtheycanadapttothenewenvironment.

CognitiveModeling:SimulatingHumanThinkingProcedure

Cognitivemodelingisbasicallythefieldofstudywithincomputersciencethatdealswiththestudyandsimulatingthethinkingprocessofhumanbeings.ThemaintaskofAIistomakemachinethinklikehuman.Themostimportantfeatureofhumanthinkingprocessisproblemsolving.Thatiswhymoreorlesscognitivemodelingtriestounderstandhowhumanscansolvetheproblems.AfterthatthismodelcanbeusedforvariousAIapplicationssuchasmachinelearning,robotics,naturallanguageprocessing,etc.Followingisthediagramofdifferentthinkinglevelsofhumanbrain:

Cognitive

Behaviora

Physical

Kinematic

Geometri

Agent&Environment

Inthissection,wewillfocusontheagentandenvironmentandhowthesehelpinArtificialIntelligence.

Agent

Anagentisanythingthatcanperceiveitsenvironmentthroughsensorsandactsuponthatenvironmentthrougheffectors.

Ahumanagenthassensoryorganssuchaseyes,ears,nose,tongueandskinparalleltothesensors,andotherorganssuchashands,legs,mouth,foreffectors.

Aroboticagentreplacescamerasandinfraredrangefindersforthesensors,andvariousmotorsandactuatorsforeffectors.

Asoftwareagenthasencodedbitstringsasitsprogramsandactions.

Environment

Someprogramsoperateinanentirelyartificialenvironmentconfinedtokeyboardinput,database,computerfilesystemsandcharacteroutputonascreen.

Incontrast,somesoftwareagents(softwarerobotsorsoftbots)existinrich,unlimitedsoftbotsdomains.Thesimulatorhasaverydetailed,complexenvironment.Thesoftwareagentneedstochoosefromalongarrayofactionsinrealtime.Asoftbotisdesignedtoscantheonlinepreferencesofthecustomerandshowsinterestingitemstothecustomerworksintherealaswellasanartificialenvironment.

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AIwithPython

AIwithPython–GettingStarted

Inthischapter,wewilllearnhowtogetstartedwithPython.WewillalsounderstandhowPythonhelpsforArtificialIntelligence.

WhyPythonforAI

Artificialintelligenceisconsideredtobethetrendingtechnologyofthefuture.Alreadythereareanumberofapplicationsmadeonit.Duetothis,manycompaniesandresearchersaretakinginterestinit.ButthemainquestionthatariseshereisthatinwhichprogramminglanguagecantheseAIapplicationsbedeveloped?TherearevariousprogramminglanguageslikeLisp,Prolog,C++,JavaandPython,whichcanbeusedfordevelopingapplicationsofAI.Amongthem,Pythonprogramminglanguagegainsahugepopularityandthereasonsareasfollows:

Simplesyntax&lesscoding

PythoninvolvesverylesscodingandsimplesyntaxamongotherprogramminglanguageswhichcanbeusedfordevelopingAIapplications.Duetothisfeature,thetestingcanbeeasierandwecanfocusmoreonprogramming.

InbuiltlibrariesforAIprojects

AmajoradvantageforusingPythonforAIisthatitcomeswithinbuiltlibraries.PythonhaslibrariesforalmostallkindsofAIprojects.Forexample,NumPy,SciPy,matplotlib,nltk,SimpleAIaresometheimportantinbuiltlibrariesofPython.

Opensource:Pythonisanopensourceprogramminglanguage.Thismakesitwidelypopularinthecommunity.

Canbeusedforbroadrangeofprogramming:Pythoncanbeusedforabroadrangeofprogrammingtaskslikesmallshellscripttoenterprisewebapplications.ThisisanotherreasonPythonissuitableforAIprojects.

FeaturesofPython

Pythonisahigh-level,interpreted,interactiveandobject-orientedscriptinglanguage.Pythonisdesignedtobehighlyreadable.ItusesEnglishkeywordsfrequentlywhereasotherlanguagesusepunctuation,andithasfewersyntacticalconstructionsthanotherlanguages.Python'sfeaturesincludethefollowing−

Easy-to-learn−Pythonhasfewkeywords,simplestructure,andaclearlydefinedsyntax.Thisallowsthestudenttopickupthelanguagequickly.

Easy-to-read−Pythoncodeismoreclearlydefinedandvisibletotheeyes.

Easy-to-maintain−Python'ssourcecodeisfairlyeasy-to-maintain.

Abroadstandardlibrary−Python'sbulkofthelibraryisveryportableandcross-platformcompatibleonUNIX,Windows,andMacintosh.

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InteractiveMode−Pythonhassupportforaninteractivemodewhichallowsinteractivetestinganddebuggingofsnippetsofcode.

Portable−Pythoncanrunonawidevarietyofhardwareplatformsandhasthesameinterfaceonallplatforms.

Extendable−Wecanaddlow-levelmodulestothePythoninterpreter.Thesemodulesenableprogrammerstoaddtoorcustomizetheirtoolstobemoreefficient.

Databases−Pythonprovidesinterfacestoallmajorcommercialdatabases.

GUIProgramming−PythonsupportsGUIapplicationsthatcanbecreatedandportedtomanysystemcalls,librariesandwindowssystems,suchasWindowsMFC,Macintosh,andtheXWindowsystemofUnix.

Scalable−Pythonprovidesabetterstructureandsupportforlargeprogramsthanshellscripting.

ImportantfeaturesofPython

LetusnowconsiderthefollowingimportantfeaturesofPython:

ItsupportsfunctionalandstructuredprogrammingmethodsaswellasOOP.

Itcanbeusedasascriptinglanguageorcanbecompiledtobyte-codeforbuildinglargeapplications.

Itprovidesveryhigh-leveldynamicdatatypesandsupportsdynamictypechecking.

Itsupportsautomaticgarbagecollection.

ItcanbeeasilyintegratedwithC,C++,COM,ActiveX,CORBA,andJava.

InstallingPython

Pythondistributionisavailableforalargenumberofplatforms.YouneedtodownloadonlythebinarycodeapplicableforyourplatformandinstallPython.

Ifthebinarycodeforyourplatformisnotavailable,youneedaCcompilertocompilethesourcecodemanually.Compilingthesourcecodeoffersmoreflexibilityintermsofchoiceoffeaturesthatyourequireinyourinstallation.

HereisaquickoverviewofinstallingPythononvariousplatforms−

UnixandLinuxInstallation

FollowthesestepstoinstallPythononUnix/Linuxmachine.

OpenaWebbrowserandgoto

/downloads/

.

FollowthelinktodownloadzippedsourcecodeavailableforUnix/Linux.

Downloadandextractfiles.

EditingtheModules/Setupfileifyouwanttocustomizesomeoptions.

run./configurescript

make

makeinstall

ThisinstallsPythonatthestandardlocation/usr/local/binanditslibrariesat/usr/local/lib/pythonXXwhereXXistheversionofPython.

WindowsInstallation

FollowthesestepstoinstallPythononWindowsmachine.

OpenaWebbrowserandgoto

/downloads/

.

FollowthelinkfortheWindowsinstallerpython-XYZ.msifilewhereXYZistheversionyouneedtoinstall.

Tousethisinstallerpython-XYZ.msi,theWindowssystemmustsupportMicrosoftInstaller2.0.SavetheinstallerfiletoyourlocalmachineandthenrunittofindoutifyourmachinesupportsMSI.

Runthedownloadedfile.ThisbringsupthePythoninstallwizard,whichisreallyeasytouse.Justacceptthedefaultsettingsandwaituntiltheinstallisfinished.

MacintoshInstallation

IfyouareonMacOSX,itisrecommendedthatyouuseHomebrewtoinstallPython3.ItisagreatpackageinstallerforMacOSXanditisreallyeasytouse.Ifyoudon'thaveHomebrew,youcaninstallitusingthefollowingcommand:

$ruby-e"$(curl-fsSL/Homebrew/install/master/install)"

Wecanupdatethepackagemanagerwiththecommandbelow:

$brewupdate

NowrunthefollowingcommandtoinstallPython3onyoursystem:

$brewinstallpython3

SettingupPATH

Programsandotherexecutablefilescanbeinmanydirectories,sooperatingsystemsprovideasearchpaththatliststhedirectoriesthattheOSsearchesforexecutables.

Thepathisstoredinanenvironmentvariable,whichisanamedstringmaintainedbytheoperatingsystem.Thisvariablecontainsinformationavailabletothecommandshellandotherprograms.

ThepathvariableisnamedasPATHinUnixorPathinWindows(Unixiscase-sensitive;Windowsisnot).

InMacOS,theinstallerhandlesthepathdetails.ToinvokethePythoninterpreterfromanyparticulardirectory,youmustaddthePythondirectorytoyourpath.

SettingPathatUnix/Linux

ToaddthePythondirectorytothepathforaparticularsessioninUnix−

Inthecshshell−typesetenvPATH"$PATH:/usr/local/bin/python"andpressEnter.

In the bash shell (Linux)− type exportATH="$PATH:/usr/local/bin/python"andpressEnter.

Intheshor