WebserviceisDashLaneforas a passwordmanagerandLynnowedas a cloudserver, and I'llcomebackinthemiddleoflivestreamandtalktoyou a bitmoreaboutthesponsorsandshowyousomeclipsandthingsfeaturesthattheyhaveandtellyouaboutthecouponcodes.
Okay, sohuhum, consolelog.
HelloworldsaysCybertron.
Nocybercrime.
Itis, butstill a bitlow, andNathaninthechatis, Well, it's Ah, Nathanis a veryloyalviewerwhohasreallybeengettingatmetodosome, uh, upgradingoftheaudioequipmentthat I haveisactuallyquitegood.
I believe I have a labmighthearactually a shotgunmikeovertherethat I don't useButwhat I reallyneedtodoissomefinetuningoftheaudio.
I use a pieceofsoftwarecalledOpenBroadcastStudio, Actually.
Check.
I don't believe I'm recordinganythingtodiskrightnow.
I'm gonnaaddthatit's righthere.
I'm gonnastartrecordingonandthefocusisalsodone.
A point.
Youknow, I I'm outofmymouthofpracticehere.
It's Saturdaymorning, and I justlike, what's goingon?
I shouldbeathomehavingbrunchandputtingmyreading a nicemagazineorbookandlisteningtosomejazzmusicontheradio.
Uh, youusethis?
Not a sponsor, butfavoriteoneofmyfavoriteproductscalledtheStreamdeck, whichisbytoolforfocusing, because I putitoverthereandthen I walkovertothecameraand I focusonit.
Uh, therewego.
I thinkthat's probablymyeyesightisactuallyquitebad.
Ifyougotothecodingtraindotcomslashtmforteachablemachine, we'lltakeyouto a Webpage, whichhasthreevideosthat I actuallytwovideosthat I releasedthisweekandonethat's stillsittingonthechannelasunlisted.
Otherpeopleareaskingfortheaudiotobe a littlebitlouder.
So I don't knowwhatyourpreferences, butifyouwannalearnhowitworks, I woulddefinitelyrecommendyouwatchtheirsinsteadofmine.
Ifyouwanttowatchsomebodyembarrassthemselvesfor 15 or 20 minutes, thenyoucanwatchmine, Um, somewonderfulprojects.
Andwhat?
What?
I'm excited.
Onethings I'm veryexcitedaboutishowthey'veintegratedtheteachablemachinemachinelearningmodelswithalltheseotherlibrariesandframeworks, inparticularthe P fiveJessLibrarywiththeMlfivelibrary.
So I don't wannagothroughthisnow.
Itreallyrelatestowhat I dowanttodointhissession, whichis, uh, lookat a particularfeatureoftheMLfivelibraryonthatalsodealswithtraining a model.
But I wouldencourageyoutocheckoutmyvideos.
Andinparticular, I wouldreallylovetoseewhatpeoplemakewiththis.
I mean, I lovethatforeverything, but I'm particularlycuriousastowhetherthismethodologyofworkingthisinterfaceinthebrowserthatallowsyoutotrain a modelandthendownloadthatmodelorexportuploadthatmodeltowworkwith, say, P five J s and M l five.
Solet's sayyoutrainittorecognize a bananaversusanorange.
Wouldthatstillworkwhen I lookatithereinthiscontextwiththegreenscreenbehindme?
Um, allright, so I'm here.
I amloading.
I thinktheideahereisthat I'm supposedtoplayrockpaperscissorswiththecomputer.
Yeah, I guessthecomputerisjustwinning.
Oh, no, I want I guessit's actuallydetectingtheknightedscissorsorhavingtopaper.
Itdetectedmypaper.
That's awesome.
Ofcourse I lostpaperagain.
I win.
Let's see, itdoesn't detectrock, butherewegothinksthatscissorsthinksthat's paper.
So a couplethings I wouldsayhereisthatinteraction, designwise, justhas a littlecritiquehere.
I'm kindofconfused.
Sowhat I think I understandisthat's whatthecomputer's picking.
Andthat's what I'm picking.
Butwhat I'm what I'm reallyconfusedhereisaboutthetiming.
So I feelthere's this, like, ready.
But I feellikewhatmightbehelpfulissomesortoflikeCountdowntimergetintoposition, becausewhenyouplayit, onewaytoplaythegameisrock, paper, Scissorssays, Shootlikethatkindofthing.
So I wonderifthere's somekindofwaythatitcouldstepmethroughtheprocess a bitmore.
I likethatthevideoistherebutkindoffadedintothebackground.
That's kindof I think, a niceidea, but I thinkthatmaybetherecouldbesomeotherwaystothinkabouthowtodotheinterface I alsoamreallylostinfindingmyselfbecause I thinkthisiscroppedand I would I wouldalways I wouldmirrorthevideobecauseitjustmakesinteractingwiththingsmucheasierbecauseoh, no, itismirrored.
Itismirrored.
Stephaniemirrored.
I justwasOh, I see.
Maybeit's doingthatonpurposesothatif I putsothattherewego I seethisiswhatitwantsmetodo.
Somaybetherecouldbetherecouldbe a bitof a stagewhereitletsyoukindofgetset.
Anditseemsthere's a momentalsowhereit's likefreezing.
Andthat's where I findthatverydistractingeso.
I kindofwanttoseeitalwaysgreat.
So I wanttoseemoreofthese.
Oh, Mika's inthechat.
Thetimeristhepinkbaratthetop.
Okay, I gotit.
I see.
I see.
AndSimonissayingthattherehavebeen a bunchofcommunitycontributionsfromtheinteractivedrawingvideo.
Somaybe I will.
Let's go, Let's go.
Let's gotake a quickpeekatthat.
Onething I needtodoso I havethisiPadherewhere I canplayandthecold.
Let's conjecture.
Okay.
Okay, everybody, settledown.
Settledout.
Um, itonlyhas 2% batteryleft, so I'm goingtounplugGoplugoverhere.
So I won't haveanymusicfor a littlewhilewhenweletthischargeup, butit'llchargeupbyhopefullythetimethat I needmusic.
I made a versionofthislikethismyselfjusttomake a gifttopostonTwitter, butthisoneisactuallyanimatingit.
I forgotthatmyvideodrilldoesn't animateit, sothat's wonderful.
Thankyouforthat.
Um, colatreerefresh.
Oh, sod.
Where's thetree?
Whyisitshowingmeallthisnonsense?
Okay, I'm notsurewhat's happeningwiththisone.
Wecanclickonlookingatthecodeandtryrunningithere.
Youhavetoclick.
I probablytoclickorsomething.
No, I'm notsurewhat's goingonhere.
Um, Donna, weletmeknow.
I'm happytotryshowingitagain.
Um, thisisAh, Cole.
Lotsvisualizationfrom a spectralflameAddedcodeforanimatedandstaticdrawing.
Soonething I wouldcertainlyrecommendifyoucan, let's see, isthiotoreadmefilewith, like, a giftanimationor a screenshotthatscrolldownthepagesaysSimon, Letmegobacktothatone.
Thecoal, it's growingtree.
Let's gobacktoAh, itwasjustItwasjusttakingup a lotofspace.
Okay, I thinkif I'm rightspectralflame, maybeyoualsocommentedintheactualYouTubevideo.
Somebodywrote a reallyexcellentcommentaryaboutsomewherethat I read.
ItwasonTwitterontheYouTubevideo.
Ormaybeitwasuhoh, baby.
ThiswastheconversationwehadonGetHub.
ButonmaybewithSpectraflamingapologies, itwassomebodyelsewhoreallydiditturn a deepdiveandfiguringoutwhatwerethepropertiesofthevisualizationfromthenumberfilevideoandhowthoseweredifferentfromtheonesthat I theversionthat I createdonlookslikethere's a reallyniceexplanationofthathereandplayedaroundwithsomemoreandgotthiscolorfulartworkandequals.
It's alwayshardtoread.
FivemillionChangethecolorplowtoincludeallcolors.
Wow, lookatthat.
ThatisquitesomethingtechniqueCollinsisasking, um, wherecan I getthedocumentationforthequickdrawproject?
So I'm notsureexactlywhatyou'rereferringto.
Butifyou'rereferringtotheactualquickdrawdatasetthatisalsofromGoogleCreativeLab, andthere's a gethubrepothathasallofthedocumentationofthequickdrawdataset.
Ifyou'relookingforinformationrelatedtomyvideototwirl, thatmakesuseof a machinelearningmodelcalledSketchareinend, whichwastrainedonthequickdrawdataset.
Thenyoucanfindthatatthecodingtraindotcom.
If I gotothistheChallengepageandtypically I mean, sometimesthingsaremissinghere, andiftheyare, youcanfileanissueoractuallysubmitthelink.
Butalloftherelevantlinksrelatedtothematerialthat I useshouldshowuphereothervideosthatarerelatedtoshowuphereandthencommunitycontributions.
Butifyou'relookingforthecode, youcouldfindthathereand a lotoftime.
MygoalistoalwayshaveJavaScriptcodeprocessingcodeand a linktotheversionrunningintheWebeditor.
Butthisonehasnoprocessingcodebecause I don't currentlyhave a Java.
Ifyouwanttodothat, youcandothatwiththethediscussioninmyMLfivevideoabouttransferlearningwiththefeatureextractorandthenrunningyourownfeature X factorclassificationexample.
Thisisbasically a bitmorethat's thatintermsofthetacticalmaterialthatyouwouldneedtoactuallycreatethetraininginterfaceandcontrolthetrainingprocessyourself.
Maurclosely.
I'm sosorrythattooksolongtopullthatup.
Andwhat I wanttodotodayisactuallyaddmakecontenttogothrough a bunchofexamplesinthislivesessionthatwillgetediteditdownintovideosthatwillendupinthisplaylistabouttraining a neuralnetworkmodel.
I guess I couldtrytogetit, keepitpluggedin, haveanythingthatthiscouldconnectThio.
Notreally.
There's noplugclosinguphere.
Justlookingatmynotesformyclasssomewhere.
Okay, I think I'm gonnadothisstuff.
Soincaseyou'rewonderingwhat I'm lookingat, I'm teaching a courseat N Y.
U thissemestercalledIntroductiontoMachineLearningfortheArts.
And I'vebeenpreparing a lotofmaterialanddoing a lotofteachinginthecourseaboutit.
And I haven't beenabletokeepmymyplanhosttobemakingvideosforthecourseallsemesterlongandandtosomeextent I'vebeendoingthat.
But I gotwaybehind, so I'm kindofgoingbacktoremindmyselfwhat I didinclassandsortofdecidinghowtohowthatisgoingtofeedintowhat I wanttoshowinthisparticularsetofvideos.
Um, andso I think I think I'm readytogo.
Andtheotherthing?
I wanttodowhat I'veuponeupgrade I'vemadetomyrecording.
A system.
Uhhuh.
Um, isthathave, um, way.
And I'm abouttoturnthisonofrecordingallthedifferentfeedstodiskseparately, greenscreen, thelaptopscreenandthewhiteboard.
AndsothisIf I'm gonnaeditIfmysay I IfMacha, whodoesthevideoeditorforthecoatingtrainisgoingtoeditallthisstufftogether, it's actuallyreallyhelpfultohavealltheseofseparatethingsincasewewantto, like, addsomemorecontentandfixsomethingsup.
Okay, so I'm justlookingintheset, so I shouldSo I needtorecord.
Um, outputShoot.
Sorry.
Giveme a secondtoyourapologiestoeveryonethat I'm doingthisduringthestream, but, uhokay.
Wait, No, no, no, no, no, no, no.
Okay, sooutputtoisthewhiteboard.
Outputthreeisthegreenscreen.
Outputfouristhelaptop.
Andsoif I gotomymultiquarterand I say I want 23 andfour, um, now I'm goingtostartrecording, and I'm recordingeverything.
Okay.
Uh, allright.
So I'm tryingtothinkofhow I wanttogoaboutthisisthenicethings, sothatthisisgoodandbad.
Thegoodnewsis I haveMaurpossibilitiesforcreatinghigherqualityeditedversionsofthelifestreamlater, because I nowhavethecapabilitytoevenif I'm showingyouthingsandtalkingaboutsufferingLifestream, I canreplacethebackgroundwith, um, differentcontentormorezoomedinandhighlightedcontent, oreven, likeotheranimationsandotherthings.
So I couldmentionsomething, notevenshowit, andthenshowitlater.
Sothat's thegoodnews.
Thebadnewsforyouisthat I don't wanttofallinthetrapofthenjustnotevershowinganythingintheLifestream.
And I don't wantalsomaketheprocessofeditingandputtingtogetherthevideossoonerousthatitbecomessoslow.
I'm alsolikegetting a lotoffeedbackfrommymonitor, Soletmejustmutethis, Okay?
Great.
Umokay.
So, um, what I'm goingtotalkabouttodayisandMlfiveneuralnetworkclass.
WannalookatthisfunctionalityandmlfivelibrarycalledMlfiveNeuralNetworkItis a functionandEmmafive, thatcreates a emptyorblank, sotospeak, neuralnetwork.
Mosteverythingthat I'veshowedyouinthisvideo, Siri's sofarhasinvolvedloading a pretrainedmodel.
So a neuralnetworkarchitecturethat's alreadybeentrainedwithsomedata.
Andinthisvideo, I wanttolookatmakinganempty a blankslate, configuring a neuralnetwork, collectingdata, trainingthemodelanddoinginferenceandthecontextthat I wanttolookatthatiswithreallytimeInteractivated.
So I'm gonnacomebackandmaybeuse a moretraditionaldatasets.
There's a datasetthatthat's ontheMLfiveexampleswiththeTitanicsurvivaldataset.
I havethedatasetfrommycolorclassifier, Siri's, so I'llcomebackandshowyousomeexamplesofthoseaswell.
Butinthisfirstvideo, I justwanttodosomethingverygeneric, whichiscreate a blankneuralnetwork, usemouseclickstotrainitandthenthenmovethemousearoundforit.
Tomakeguessesarepredictions.
Andthatmightsoundlike a weirdthingtodoandhopefullystarttomakesenseas I buildthecodeandstepthroughalltheprocesses.
Allright, sothatwasmybeginningopeningdiscussion.
I didexactlywhat I thought.
It's sortof a problem, whichisthat I didn't showyouanythinglike I didn't like, clickandbrowsearoundthewebsiteandfindstuff.
But I dowanttoaddthatinlater.
We'llseehowthatworks.
Allright, um, I doseethatthereis a suggestionabouttheaudiocontextinJavascript.
Itwon't behappeningtoday.
I appreciateeveryone's enthusiasmandwantingtohavetheirideashownortalkedabout, but I'm on a particularpath, and I'm justdoingthetopicthat I'm doingintheabsolutelycomputationalgeometryisonmylist.
Antireflectivecoatingsuppliedontheirglasses.
I thought I hadthat, but I willgetit.
I'm gonnagogetnewglasses.
It's anotherthingformyupgrading.
Howbadisthereflectionrightnow?
Becausethereis a waythat I canturnthelightawayforme.
Andifyouwalktheteachablemachine, Siri's thethirdvideoHasthelightturnedawayfromme, anditdoesn't reflectbutthenelseofthiswayofshadowonmyface, I don't know.
Um, I wasgonna I wanttotalkaboutRebeccaFiBrinkandUekiNadir.
So, um, letmetalkaboutthat.
Umand, uh, allright, thereflectiondoesn't bother.
Okay.
Um, allright.
So I alsowant a highlightforyoutheUekiNaderproject, whichis a free, opensourcepieceofsoftwarecreatedbyRebeccaFreeBrakein 9 2004 Trainingmachinelearningmodels.
And I wouldespeciallyencourageyoutowatchRebeccaFibringstalkfromthe i o conferencein 2018 whereshetalksaboutcreativityandinclusionandmachinelearning, andgoesthroughsomedemonstrationsofwithUeki, Naderandprocessingandotherpiecesofsoftware.
So a lotoftheworkthat I'm doingwithMlfiveisisentirelybasedonrecreationsofmanyoftheexampledemonstrationsthatRebeccaFiBrinkmadeandhasdoneresearchaboutforyearsandyearswiththeWECAnEaterproject.
Soinfact, theexamplesthat I'm goingtomakeinthisvideoandthenextoneandthenextfollowupsaredirectportsin a wayofsomeoftheoriginalUeki, Naderandprocessingexamples.
But I'm gonnadoitallinJavaScriptinthebrowserwith P fiveandtheMlfiveJazzLibrary.
Um, I thinkwhat I'llsayalsois.
And, um, there's also a fairlylengthyhistoryofcreativeartistsusingrealtime a trainingmachinelearningmodelsinrealtime.
Letmeseethat.
Umuh, there's also a longThere's also a fairlylengthyhistoryofcreativeartiststrainingmachinelearningmodelsinrealtimetocontrolmusicalinstrumentsofperformance.
Ah, visualartpiece.
And I wouldencourageyoutocheckoutsomeoftheseprojectsMartlitbyMichele, theguyfromthewatersbyanhedge.
Thisisnot a fairamendbyGuillermoMontesinosinSofiaSuazoandtheeyeconductorbyunder s restguardthat I willlinktointhisvideo's descriptionforinspirationandideas.
Um, okay, sonow, though, um, let's seehere.
Umletmejustquicklygodothegettingstarted.
Copythis.
I justwanttogetthelibraryinthe p fivesketch.
Okay, herewego.
Um, Andhowam I ontime?
11.
20.
Allright.
Uhhuh.
Say, Levy, Um, am I like, I don't thinkthiscameraisparticularlylevel, butit's fine, right?
Um, Okay, uh, ourguideforfiguringouthowtowritethecodeisgoingtobethemlfivewebsite, andthere's a pageonthemlfivewebsitefortheneuralnetworkfunction.
Butbefore I startdivingtothecode, let's take a minutetotalkaboutwhat a neuralnetworkisnow.
Bynomeansam I gonnabecomprehensiveaboutthis?
Atthismoment?
Infact, I'm goingtogiveyou a veryzoomedout, highleveloverview, and I wouldreferyoutothethreeblueonebrownvideo.
Siri's whatis a neuralnetworkwhichisoneofthemostexcellentvideosontheInternetTojustquicktosuccinctlyexplainedingreatdepthwhat a neuralnetworkis.
And I havegonethroughmanydifferentplaylists.
I guess I shouldbedoingthisinfrontofthegreenscreenkiss.
I wanttoshowanyofthisstuffaboutYeah.
Oh, justdoitoverhere.
What, yougonnasaythisagain?
Now, bynomeansam I goingtogiveyou a comprehensiveexplanationNow, bynomeansinthisvideoam I goingtodo a comprehensivedeepdiveintowhat a neuralnetworkisandhowtocodeonefromscratch.
I willreferyoutomanyotherwonderfulresourceiswhereyoucoulddothatdeepdive, startingwiththethreeblueonebrownvideo.
Whatis a neuralnetworkandsomeofthesubsequentones?
I havealsohave a 10 to 15 partvideo.
Siri's where I build a neuralnetworkfromscratchinJavascriptbasedon a particularbookcalledMakeYourOwnNeuralNetwork, thatis, inPython.
I haveothervideoswerethatourguidesaroundmachinelearningconceptswhere I talkaboutdifferentkindsofneuralnetworks.
So I willlinktoallofthoseinthisvideo's description.
Buthere, I'm gonnausethewhiteportoverherejusttogiveyou a veryzoomedout, highleveloverviewofwhat I'm talkingabout.
So a machinelearningsystem, inthemostbasicsenseinvolvesinputsandoutputs, A classicexampleof a datascienceapproached a machinelearningmightbe.
Wewanttohavesomesortofmachinelearningmodelthatcanpredictthepriceof a housebasedonsomesetoffactors.
Thoseinputswouldbefedintothemachinelearningmodel, andtheoutputwouldbe a numberahpriceonthis, bytheway, iscalled a regression, whichsoundslike a sortofterrifyingterm.
Andsomehow I havetobe a PhDandstatisticsunderstandregression.
Butwhat I meaninthiscase, a regressionistheoutputissomecontinuousnumber.
Uh, it's a price.
Itcouldbezero.
Itcouldbe 100.
Itcouldbe 1.5 million.
It's somenumber, whichisdifferentthantheoutputbeing a classification, meaningitisoneofseveralcategories.
It's a cator a dogor a turtleoritsClass A orClass B orClass C.
Soifyou'vewatchedmyrecentteachablemachinevideo, Siri's abouttraininganimageclassifier, a soundclassifier.
Allofthoseexamplesareclassificationsoutputs.
Theoutputthatyougetis a setofconfidencescoresandcategories.
Um, interestinglyenough, I startedwiththisdiscussion, saying I wasgoingtogiveyou a highleveloverviewofwhat a neuralnetworkis, and I haven't evenbegunthatbecause I startedtalkingabout a highleveloverviewofthemachinelearningpipeline.
Theprocess.
So, in a way, that's whatthisvideoisalsoabout, andthewaythat I thinkmightbeineffective.
Yes.
Andaneffectivewaythat I mightbeabletodemonstratethistoyouisToekindistofindthemostdropdeadsimple, almosttrivialscenariotoshowyouallofthosepieces.
Thisis a scenariothat's coveredingreatdetailinRebeccaFibringscoursemachinelearningforartistsandmusicians.
A verysimpleonewaythat I mightboilthisideadownintoitsverysimplestversionisThinkabout a two D canvassandit's veryconvenientthat I'm using p fivebecausethat's thethingthatexistsin P five J s.
I have a two d canvassAndwhat I'm goingtodois I'm goingtosaythere's a mouseinthatcanvasandthemouseisgoingtomovearoundthecanvas.
Andbasedonwhereitis, itwillplay a particularnote.
Now, ofcourse, I coulddothiswithifstatementsveryeasily.