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Using Deep Learning To Predict Performance FromResumes
Ben Taylor, Chief Data Scientist
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INTRODUCTIONS
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Ben Taylor @bentaylordata
Background Personal
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• Sequoia Capital
• Largest Video Interviewing Platform
• Forbes #10 most promising companies
• Global: 189 countries
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NATURAL LANGUAGE PROCESSING (NLP)
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GRIT MOTIVATION ENGAGEMENT PERFORMANCE
1 55 80 95%
0 75 10 22%
0 50 20 57%
1 20 90 91%
0 40 60 11%
BasicTutorialOnHowToBuildANumericFeatureModel
BUILDING A MODEL
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ESSAY GRIT MOTIVATION ENGAGEMENT PERFORMANCE
I want to work here 1 55 80 95%
I have great teamwork 0 75 10 22%
Synergy 0 50 20 57%
I have so much grit 1 20 90 91%
They fired that individual 0 40 60 11%
Now what?!?
BUILDING A MODEL
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ESSAY PERFORMANCE
I want to work here 95%
I have great teamwork 22%
Synergy 57%
I have so much grit 91%
They fired that individual 11%
There are really two different options, mapping or tokenizing
BUILDING A MODEL
Map:Bad=0Good=1Better=2Best=3
Tokenize:Female=1Male=1
Female Male
1 0
0 1
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I want to work here have great PERF.1 1 1 1 1 0 0 95%1 0 0 0 0 1 1 22%0 0 0 0 0 0 0 57%1 0 0 0 0 1 0 91%0 0 0 0 0 0 0 11%
Tokenizethetextintouniquewordcolumns
BUILDING A MODEL
ESSAY PERFORMANCE
I want to work here 95%
I have great teamwork 22%
Synergy 57%
I have so much grit 91%
They fired that individual 11%
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I want to work here have great PERF.1 1 1 1 1 0 0 95%1 0 0 0 0 1 1 22%0 0 0 0 0 0 0 57%1 0 0 0 0 1 0 91%0 0 0 0 0 0 0 11%
Bagofwordsmodeling,sequenceandorderingislost
BUILDING A MODEL
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Bagofwordsmodeling,sequenceandorderingislost
BUILDING A MODEL
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I want Want to to go work here PERF.
1 1 1 1 1 95%1 0 0 0 0 22%0 0 0 0 0 57%1 0 0 0 0 91%0 0 0 0 0 11%
Band-Aid:Conceptofn-grams
BUILDING A MODEL
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SENTIMENT EXAMPLE(multiclass)
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Weneedalabeleddataset,sometimesgettingonewithlabelsisthebiggestchallengeofall.
SENTIMENT DATASET, 1.5M TWEETS
label textneg @Christian_Rocha i miss u!!!!!pos @llanitos there's still some St Werburghs hone...pos @Ashley96 it's meneg @Phillykidd we use to be like bestfriends
negJust got back from Manchester. I went to the T...
pos @LauraDark thnks x el rt
neg"Ughh it's so hot & the singing lady is st...
neg@hnprashanth @dkris I was out to my native for...
pos Girls night with the bests Wish you were here J!
negJust watched @paulkehler rock the crap out of ...
pos i got the gurl! i got the ride! now im just on...pos @ninthspace how is the table building going?pos by d way guyz I must log out na see u again to...neg @dreday11 its only 20 mins...
Sentiment140 cs.stanford.edu:( :)
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Beforewecanprocessthisweneedtodotheproperformattingtogetitready
SENTIMENT DATASET - FORMATTING
text@Christian_Rocha i miss u!!!!!@llanitos there's still some St Werburghs hone...@Ashley96 it's me@Phillykidd we use to be like bestfriendsJust got back from Manchester. I went to the T...@LauraDark thnks x el rt"Ughh it's so hot & the singing lady is st...@hnprashanth @dkris I was out to my native for...Girls night with the bests Wish you were here J!Just watched @paulkehler rock the crap out of ...i got the gurl! i got the ride! now im just on...@ninthspace how is the table building going?by d way guyz I must log out na see u again to...@dreday11 its only 20 mins...
Pythonlist
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Nowwecangoallthewaytomodeltrainingandprediction
SENTIMENT DATASET – UNIGRAM
y[0,1,0,1,1]
text_data[[‘thisisatweet’][‘soundsgood’][‘notreally’]]
I want to work here have great1 1 1 1 1 0 01 0 0 0 0 1 10 0 0 0 0 0 01 0 0 0 0 1 00 0 0 0 0 0 0
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Nowwecangoallthewaytomodeltrainingandprediction
SENTIMENT DATASET – BIGRAM
I want Want to to go work here
1 1 1 1 11 0 0 0 00 0 0 0 01 0 0 0 00 0 0 0 0
text_data[[‘thisisatweet’][‘soundsgood’][‘notreally’]]
y[0,1,0,1,1]
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BUILDING A MODEL
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Convertlabelstointegers
SENTIMENT DATASET - FORMATTING
Pythonintarray
labelnegposposnegnegposnegnegposnegposposposneg
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Convertlabelstointegers
SENTIMENT DATASET - FORMATTING
model.fit(X,Y)
X[4,0,0,0,0,7,0,0,1][0,0,0,0,9,0,0,0,2]
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Nowwecangoallthewaytomodeltrainingandprediction
SENTIMENT DATASET – BUILD A MODEL
y[0,1,0,1,1]
X[4,0,0,0,0,7,0,0,1][0,0,0,0,9,0,0,0,2]
PERFORMANCE?
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DON’T CHEAT!
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PROPER MODEL VALIDATION
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Weneedtoholdoutdatawecantestagainst,thisiscalledyourvalidationset
SENTIMENT DATASET – VALIDATION
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Trainon20%,teston80%
SENTIMENT DATASET – VALIDATION
20% 80%
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Bestscoreyet
SENTIMENT DATASET – VALIDATION
60% 40%
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Bestscoreyet
SENTIMENT DATASET – VALIDATION
70% 30%
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Bestscoreyet
SENTIMENT DATASET – VALIDATION
80% 20%
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Bestscoreyet
SENTIMENT DATASET – VALIDATION
99% 1%
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Perfectscores
SENTIMENT DATASET – VALIDATION
99.9999% 2
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Predict Every Point, k-foldingFolds = 9 Fold = 1 Fold = 2… Y_pred
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SENTIMENT DATASET – Validation
10 folds
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SENTIMENT DATASET – Validation
100 folds
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BIGRAM BOOST
acc: 0.8015r: 0.2061AUROC: 0.8738
acc: 0.7809r: 0.1238AUROC: 0.8554
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Feature Creation
Model Selection
Feature Reduction
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BETTER MODELS
acc: 0.8208r: 0.2832AUROC: 0.8939
acc: 0.8015r: 0.2061AUROC: 0.8739
Was:
Now: (10x average)
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EMAIL CLASSIFICATION(multiclass)
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EMAIL MULTICLASS DATASET (20 classes)
alt.atheismcomp.graphicscomp.os.ms-windows.misccomp.sys.ibm.pc.hardwarecomp.sys.mac.hardwarecomp.windows.xmisc.forsalerec.autosrec.motorcyclesrec.sport.baseballrec.sport.hockey
sci.cryptsci.electronicssci.medsci.spacesoc.religion.christiantalk.politics.gunstalk.politics.mideasttalk.politics.misctalk.religion.misc
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EMAIL MULTICLASS DATASET (20 classes)
From: [email protected](where'smything)Subject: WHATcaristhis!?Nntp-Posting-Host: rac3.wam.umd.eduOrganization: UniversityofMaryland,CollegeParkLines: 15MSG: I was wondering if anyone out there could enlighten me on this car I saw\nthe other day. It was a 2-door sports car, looked to be from the late 60s/\nearly 70s. It was called a Bricklin. The doors were really small. In addition,\nthe front bumper was separate from the rest of the body. This is \nall I know. If anyone can tellme a model name, engine specs, years\nof production, where this car is made, history, or whatever info you\nhave on this funky looking car, please e-mail.\n\nThanks,\n- IL\n ---- brought to you by your neighborhood Lerxst ----\n\n\n\n\n"
rec.autos
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EMAIL MULTICLASS DATASET (20 classes)
From: [email protected](GuyKuo)Subject: SIClockPoll-FinalCallSummary: FinalcallforSIclockreportsKeywords: SI,acceleration,clock,upgradeArticle-I.D.: shelley.1qvfo9INNc3sOrganization: UniversityofWashingtonLines: 11NNTP-Posting-Host: carson.u.washington.eduMSG: AfairnumberofbravesoulswhoupgradedtheirSIclockoscillatorhave\nsharedtheirexperiencesforthispoll.Pleasesendabriefmessagedetailing\nyourexperienceswiththeprocedure.Topspeedattained,CPUratedspeed,\naddoncardsandadapters,heatsinks,hourofusageperday,floppydisk\nfunctionalitywith800and1.4mfloppiesareespeciallyrequested.\n\nIwillbesummarizinginthenexttwodays,sopleaseaddtothenetwork\nknowledgebaseifyouhavedonetheclockupgradeandhaven'tansweredthis\npoll.Thanks.\n\nGuyKuo<[email protected]>\n"
comp.sys.mac.hardware
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EMAIL MULTICLASS DATASET (20 classes)
From: jgreen@amber(JoeGreen)Subject: Re:WeitekP9000?Organization: HarrisComputerSystemsDivisionLines: 14Distribution: worldNNTP-Posting-Host: amber.ssd.csd.harris.comX-Newsreader: TIN[version1.1PL9]MSG: RobertJ.C.Kyanko([email protected])wrote:\n>[email protected]<[email protected]>:\n>>AnyoneknowabouttheWeitekP9000graphicschip?\n>Asfarasthelow-levelstuffgoes,itlooksprettynice.It\'sgotthis\n>quadrilateralfillcommandthatrequiresjustthefourpoints.\n\nDoyouhaveWeitek\'saddress/phonenumber?I\'dliketogetsomeinformation\naboutthischip.\n\n--\nJoeGreen\t\t\t\tHarrisCorporation\[email protected]\t\t\tComputerSystemsDivision\n"Theonlythingthatreallyscaresmeisapersonwithnosenseofhumor."\n\t\t\t\t\t\t--JonathanWinters\n’
comp.graphics
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EMAIL MULTICLASS DATASET (20 classes)
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RESUME MODELING
(binary)
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Upload Your Resume
Now painstakingly fill out this form containing all of the exact same information
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Document modeling review
UNSTRUCTURED
STRUCTURED
MUNGED
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Resume Extension
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Resume format consolidation
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GPA Inclusion (18%)
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GPA Replacement
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Mimicking the human recruiterFeature Hunt
ONEFEATUREATATIME
INCREMENTAL GAINS
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DEEP LEARNING
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UnstructuredENGINEERSANDMANUALFEATURESAREEXPENSIVE,USINGDEEPLEARNINGTOAUTOMATE
AUTOMATIC FEATURE GENERATION
StructuredI want Want
to to go work here PERF.
1 1 1 1 1 95%1 0 0 0 0 22%0 0 0 0 0 57%1 0 0 0 0 91%0 0 0 0 0 11%
ESSAY
I want to work here
I have great teamwork
Synergy
I have so much gritThey fired that
individual
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ENGINEERSANDMANUALFEATURESAREEXPENSIVE,USINGDEEPLEARNINGTOAUTOMATE
AUTOMATIC FEATURE GENERATION
ESSAY
I want to work here
I have great teamwork
Synergy
I have so much gritThey fired that
individual
ESSAY
3 2 1 4 5
3 7 67 345
54
3 7 99 10234
78 203 501 14
1 2 3 4 50 0 0 1 01 0 0 0 00 1 0 0 00 0 1 0 0
LSTM
RAWTEXT WORDSEQUENCE
ENCODING
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AUTOMATIC FEATURE GENERATION
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AUTOMATIC FEATURE GENERATION
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AUTOMATIC FEATURE GENERATION
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BEGINSCRATCHINGATLAYOUT
AUTOMATIC FEATURE GENERATION (LAYOUT)
CNN:bit.ly/pacon
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INTERVIEW MODELING
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59
WOULDYOUEVERHIREFROM JUST ARESUME?
INTERVIEW MODELINGSOFT/TECHNICAL COMPETENCIESResumecanoverstateandunderstate
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Audio VideoText
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QUESTIONS