machine learning meets web development
TRANSCRIPT
ML is just for product engineers?Spam Mail DetectionImage Recognition (OCR)Recommendation EngineQuery SuggestionAuto CompletionImage TaggingWord IndexingFraud Detection
Search EngineVoice RecognitionRobot LocomotionAutomatic DiagnosisVideo Game ExpertAutomated TradingFace RecognitionPattern Recognition
Route SearchTrend ForecastingHandwriting RecognitionComputer VisionTranslationName IdentificationTransaction Data MiningHuman Modeling
ML for designers: interactive data visualization.
Shuhei Iitsuka and Yutaka Matsuo: A Product Network Based on Browsing and Purchase Behavior in E-commerce. The institute of electronics information and communication engineers D. 2015.
Wedding Venue A
Wedding Venue B
Images from:http://zexy.net/wedding/c_7770021671/http://zexy.net/wedding/c_7770029193/
User
inquiry inquiry
Competition
ML for designers: interactive data visualization.
http://colah.github.io/posts/2014-10-Visualizing-MNIST/
Example: Visualizing MNIST: An Exploration of Dimensionality Reduction
Visualization of how a machine recognize handwritten digits to classify.
ML for developers: ask users for the best one.
Image from: Autonomous Systems Labs - TU Darmstadt http://www.ausy.tu-darmstadt.de/Research/Research
Website UsersVariation
Clicks
A/B testing
ML for developers: ask users for the best one.
Example: Obama Campaign in 2010
$60M improvementhttp://blog.optimizely.com/2010/11/29/how-obama-raised-60-million-by-running-a-simple-experiment/
Example: A/B testing on BingBEFORE
$10M annual revenue improvementIitsuka, Shuhei, and Yutaka Matsuo. "Website Optimization Problem and Its Solutions." Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2015.
AFTER
ML for marketers: product mapping on preference axis.
item #1item #2・・・
item #10000
user #1, ・・・ , user #m
BUYSKIP
SEEBUY
SEE SKIP
・・・
・・・
・・・
・・・LOGDATA luxury
modern
Axis of preferen
ce
modest
old-fashioned
User behavior
Aggregation(PCA)
item #1 item
#5
item #3item
#2item #4
item #7
item #6