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Yapay Zeka ile Tüketici Davranışı Nasıl Anlamlanıyor?

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Yapay Zeka ile Tüketici Davranışı Nasıl Anlamlanıyor?
Dr. Tanju Çataltepe, Tazi.ai

Webrazzi Dijital 2019

Published in: Business
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Yapay Zeka ile Tüketici Davranışı Nasıl Anlamlanıyor?

  1. 1. N e x t G e n e r a t i o n Delivering the Promise of AI Tanju Çataltepe | CO-FOUNDER CTO | tanju@tazi.ai
  2. 2. Customer Credit Risk Score Up-sell Cross-sell Churn Prevention Demand Risk Evaluation Website Production Planning Pricing Sales New Product Service evelopment IT Service Fault Management Security CFO Invesment Planning Marketing Call Center Logistic Enterprise Processes OPERATIONAL TACTICAL STRATEGIC AI AI AI AI AI AI AI AI AI AI AI AI AI AI AI
  3. 3. AI Opportunity & Challenge Hype Cycle Global AI Opportunity $50 Billion AI-ML Spending by 2021 *International Data Corporation (IDC) $5 Trillion AI to create in value annually *McKinsey 40% Productivity & Corp. profitability *Accenture AI Fact: Data Changes Fast 37% Only 37% of today’s will be useful by 2020 5000Data Scientist 10+ Years Experience
  4. 4. AI cannot explain decisions GDPR and data privacy BIAS Data not good enough Debugging data Communication Bottleneck No in-house skills available Data scientists have no credibility Executives or LOBs don’t buy-in In-house data scientists too junior Silent fail Pure-cloud AI service Ongoing maintenance Tooling is still fragmented AI Bad News 80% Failure
  5. 5. AI Taxonomy AIA R T I F I C I A L GAI I N T E L L I G E N C E NAI Expert Systems 1980s Machine Learning Logistic Regression SVM Neural Networks Graphical Models Clustering Decision Tree Deep Learning Symbolic Logic Academia
  6. 6. AI History 1940 1950 1960 1970 1980 1990 2000 2010 2020 ISAAC ASIMOV ALAN TURING MARVIN MINSKY Perceptron (Neural Net) Symbolic Logic NLP Expert Systems Machine Learning Deep Learning Funding $$ F I C T I O N SCIENCE
  7. 7. Next Generation Auto ML ML AUTO ML NEXT GENERATION AUTO ML
  8. 8. Next Generation Auto ML Continuous Learning From Human Explainable Citizen Data Scientist
  9. 9. TAZI System Architecture Customer Reporting & BI Systems SQL, Kafka … Customer Transactions SQL, Kafka … Tazi can help to find KPI based customer microsegments at these steps < Continuous Learning, KPI Performance Reporting,
 AML Understanding & Feedback Claim Frequency/Severity Prediction Data Preparation < < Flags Performance Reporting • Check, Revise, adjust, control, Growth Prediction Model Profit-Loss Prediction Model Churn Prediction Model Prediction of whether the customer will pay in t+dt Prescription: advise who calls and with what offer Record customer, personnel actions and the results of actions Record tazi results
  10. 10. Customer Credit Risk Score Up-sell Cross-sell Churn Prevention Demand Risk Evaluation Website Production Planning Pricing Sales New Product Service evelopment IT Service Fault Management Security CFO Invesment Planning Marketing Call Center Logistic Enterprise Processes with Tazi TACTICAL STRATEGIC OPERATIONAL
  11. 11. N e x t G e n e r a t i o n THANK YOU Tanju Çataltepe | CO-FOUNDER CTO | tanju@tazi.ai

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