What is Neural Network: Overview, Applications, and ...

Applications of Neural Network · Handwriting Recognition · Stock-Exchange prediction · Traveling Issues of sales professionals · Image compression. 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Eversincethe1950s,scientistshavebeentryingtomimicthefunctioningofaneuronanduseittomakesmarterandbetterrobots.Afteralotoftrialanderror,humansfinallycreatedacomputerthatcouldrecognizehumanspeech.Itwasonlyaftertheyear2000thatpeoplewereabletomasterdeeplearning(asubsetofAI)thatwasabletoseeanddistinguishbetweenvariousimagesandvideos. Beforewetakeadetailedlookatwhatconstitutesaneuralnetwork,let’sgetarefresherontheconceptofdeeplearning. PostGraduatePrograminAIandMachineLearningInPartnershipwithPurdueUniversityExploreCourse WhatIsDeepLearning? Deeplearningisamachinelearningsubsetthatmakescomputersdowhatcomesnaturallytohumans:learnbyexample. Machinesgettrainedwithimagesasexamples,aprocessverydifferentfromhardwiringacomputerprogramtorecognizesomethingandlearn.Youdon'tcontrolhowitknows;youcontroltheaspectsthatgointoit.Thecomputeridentifiestheobjectbasedontheimagesfedearlier. Scientistsbuiltasyntheticformofabiologicalneuronthatpowersanydeeplearning-basedmachine. So,whatisaneuralnetwork? WhatIsaNeuralNetwork? Tounderstandhowanartificialneuronworks,weshouldfirstunderstandhowabiologicalneuronworks.   Dendrites  Thesereceiveinformationorsignalsfromotherneuronsthatgetconnectedtoit. CellBody Informationprocessinghappensinacellbody.Thesetakeinalltheinformationcomingfromthedifferentdendritesandprocessthatinformation. Axon  Itsendstheoutputsignaltoanotherneuronfortheflowofinformation.Here,eachoftheflangesconnectstothedendriteorthehairsonthenextone.  TheimageshownbelowdepictsanANN.  Thenetworkstartswithaninputlayerthatreceivesinputindataform. Thelinesconnectedtothehiddenlayersarecalledweights,andtheyadduponthehiddenlayers.Eachdotinthehiddenlayerprocessestheinputs,anditputsanoutputintothenexthiddenlayerand,lastly,intotheoutputlayer.  Lookingattheabovetwoimages,youcanobservehowanANNreplicatesabiologicalneuron. Inputtoaneuron-inputlayer Neuron-hiddenlayer Outputtothenextneuron-outputlayer Aneuralnetworkisasystemofhardwareorsoftwarepatternedaftertheoperationofneuronsinthehumanbrain.Neuralnetworks,alsocalledartificialneuralnetworks,areameansofachievingdeeplearning. Whenyouwanttofigureouthowaneuralnetworkfunctions,youneedtolookatneuralnetworkarchitecture. TheArchitectureofaNeuralNetwork HaveyoueveraskedSiriaquestion?Thedeviceanswersaccurately.Let’stakeacloserlookandseehowthevirtualassistantaccomplishesthisfeatofspeechrecognition. Therearefiverecognizedtypesofneuralnetworks. Single-layerfeed-forwardnetwork. Multilayerfeed-forwardnetwork. Singlenodewithitsownfeedback. Single-layerrecurrentnetwork. Multilayerrecurrentnetwork. Consider,forinstance,theneuralnetworkshownbelow,anexampleofasingle-layerrecurrentnetwork: Thereareinput,hidden,andoutputlayersonthenetwork.But,first,thenetworkneedstorecognizethesentence:Whatisthetime? Here,eachwordcomesinasapatternofsound.Then,thesentencegetssampledintodiscretesoundwaves. Let'sconsiderthefirstword:What  Youcanseethewaveformissplitbasedoneveryletter.NowwewillsplitthesoundwavefortheletterWintosmallersegments. Theamplitudevariesinthesoundwavewhenweanalyzetheletter'W,'asshownbelow. Wecollectthevaluesatintervalsandformanarray.Then,differentamplitudescomeinforotherletters,andwefeedthevarietyofamplitudestotheinputlayer. Randomweightsgetassignedtoeachinterconnectionbetweentheinputandhiddenlayers. Wealwaysstartwiththerandomkey,asassigningapresetvaluetotheweightstakesasignificantamountoftimewhentrainingthemodel.  Theweightsgetmultipliedwiththeinputs,andabiasisaddedtoformthetransferfunction.  Weightsgetassignedtotheinterconnectionbetweenthehiddenlayers.Theoutputofthetransferfunctionisfedasaninputtotheactivationfunction.Theworkfromonehiddenlayerbecomestheinputtothenext. FREEDataScienceWithPythonCourseGainMasteryinDataSciencewithPythonNowStartLearning Theacousticmodelcontainsthestatisticalrepresentationofeachsoundthatmakesaword.Sowestartbuildingtheseacousticmodels,andastheselayersseparatethem,they'llstartlearningwhatthedifferentmodelsrepresentforotherletters. Thelexiconcontainsthedatafordifferentpronunciationsofeveryword.Thelexiconisattheend,whereweendupwiththeABCD,identifyingtheotherlettersthere. Finally,wegetouroutputletter.Followingthesameprocessforeverywordandletter,theneuralnetworkrecognizesthesentenceyousaidoryourquestion. Notethattheterms“acousticmodel”and“lexicon”arespecifictothedomainofunderstandingspeech.Whendealingwithotherinputformats,you'llhavedifferentlabels,buttheprocessremainsthesame. MasterdeeplearningconceptsandtheTensorFlowopen-sourceframeworkwiththe DeepLearningCourse.Getskilledtoday! AdvantagesofNeuralNetwork ANNoutputsaren'tlimitedentirelybyinputsandresultsgiventotheminitiallybyanexpertsystem.Thisabilitycomesinhandyforroboticsandpatternrecognitionsystems. Thisneuralnetworkhasthepotentialforhighfaulttoleranceandcandebugordiagnoseanetworkonitsown.ANNcangothroughthousandsoflogfilesfromacompanyandsortthemout.Itiscurrentlyatedioustaskdonebyadministrators,butitwillsaveasignificantamountoftime,energy,andresourcesifitcanbeautomated. Nonlinearsystemscanfindshortcutstoreachcomputationallyexpensivesolutions.Weseethisinthebankingindustry,forexample,wheretheyworkonaparticularExcelspreadsheet,andastimegoesby,startbuildingcodesaroundit.Inover20years,theymightcreatearepertoireofallthesefunctions,andtheneuralnetworkrapidlycomesupwiththesameanswersotherwisedoneindays,weeks,orevenamonth,whendonebyalargebank. Sohowdoneuralnetworksapplytoday? ApplicationsofNeuralNetwork Withanenormousnumberofapplicationsimplementationseveryday,nowisthemostappropriatetimetoknowabouttheapplicationsofneuralnetworks,machinelearning,andartificialintelligence.Someofthemarediscussedbelow: HandwritingRecognition Neuralnetworksareusedtoconverthandwrittencharactersintodigitalcharactersthatamachinecanrecognize. Stock-Exchangeprediction Thestockexchangeisaffectedbymanydifferentfactors,makingitdifficulttotrackanddifficulttounderstand.However,aneuralnetworkcanexaminemanyofthesefactorsandpredictthepricesdaily,whichwouldhelpstockbrokers.  Currently,thisoperationisstillinitsinitialphases.However,youshouldknowthatoverthreeterabytesofdataadayaregeneratedfromtheUnitedStatesstockexchangealone.That'salotofdatatodigthrough,andyoumustsortitoutbeforeyoustartfocusingonevenasinglestock. FreeCourse:IntroductiontoAILearntheCoreAIConceptsandKeySkillsforFREEStartLearning TravelingIssuesofsalesprofessionals Thisapplicationreferstofindinganoptimalpathtotravelbetweencitiesinagivenarea.Neuralnetworkshelpsolvetheproblemofprovidinghigherrevenueatminimalcosts.However,theLogisticalconsiderationsareenormous,andwemustfindoptimaltravelpathsforsalesprofessionalsmovingfromtowntotown.  Imagecompression Theideabehindneuralnetworkdatacompressionistostore,encrypt,andrecreatetheactualimageagain.Therefore,wecanoptimizethesizeofourdatausingimagecompressionneuralnetworks.Itistheidealapplicationtosavememoryandoptimizeit. So,whatdoesthefutureofneuralnetworkslooklike? FutureofNeuralNetworks WiththerapidpacethatAIandmachinelearningarebeingadoptedbycompaniestoday,wecouldseemoreadvancementsintheapplicationsofneuralnetworksintheforeseeablefuture.AIandmachinelearningwillofferawealthofpersonalizedchoicesforusersworldwide.Forexample,allmobileandwebapplicationstrytogiveyouanenhancedcustomizedexperiencebasedonyoursearchhistory,andneuralnetworkscanmakethatpossible.  Hyper-intelligentvirtualassistantswillmakelifeeasier.IfyouhaveeverusedGoogleassistant,Siri,oranyotherproducts,youcanseehowthey'reslowlyevolving.Theymayevenpredictyouremailresponsesinthefuture! Wecanalsoexpectintriguingdiscoveriesonalgorithmstosupportlearningmethods.However,wearejustintheinfantstageofapplyingartificialintelligenceandneuralnetworkstotherealworld. Neuralnetworkswillbealotfasterinthefuture,andneuralnetworktoolscangetembeddedineverydesignsurface.Wealreadyhavealittleminineuralnetworkthatplugsintoaninexpensiveprocessingboardorevenintoyourlaptop.Insteadofthesoftware,focusingonthehardwarewouldmakesuchdevicesevenfaster. Neuralnetworkswillalsofindtheirwayintothefieldsofmedicine,agriculture,physics,research,andanythingelseyoucanimagine.Neuralnetworkswillalsofinditswayintothefieldsofmedicine,agriculture,physics,research,andanythingelseyoucanimagine. DoYouWantaCareerinMachineLearning? Theworldiswideopenforanybodywhowantstolearnneuralnetworksandexplorethefield'spotential.Themoreyouunderstandtheconcepts,thebetteryoucanapplythemtodifferentareasandturnthatknowledgeintoapromisingcareer. WhiletheadoptionofAIisgrowingwitheachpassingday,companiesworldwidearefacingashortageofITtalent.Simplilearn’sArtificialIntelligenceandMachineLearningBootcamp,deliveredinpartnershipwithIBMandfeaturingmasterclassesbyCaltechfacultyandIBMexperts,canhelpyoustartagreatnewcareerinthisexcitingandrapidlygrowingfield.  TheAIandMLbootcampcoversvitalconceptslikeStatistics,DataSciencewithPython,MachineLearning,DeepLearning,NLP,andReinforcementLearning,alldesignedandperfectedtoboostyourcareerasanAIandMLprofessional. AccordingtoIndeed,machinelearningengineersintheUnitedStatescanearnanaverageof$131,063peryear.PayscalereportsthatmachinelearningengineersinIndiamaybringinanannualaveragesalaryof₹732,566.Don’tdelay.CheckoutSimplilearn’smanyAIandMLcoursesandgetanexcitingandrewardingcareerinahotnewfieldofftheground! 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