A product-focused introduction to Machine Learning

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A product-focused introduction to Machine Learning

  1. 1. A product-focused introduction to Machine Learning satpreetsingh@gmail.com July 2013
  2. 2. “Beer and Diapers”
  3. 3. Unsupervised Learning: “Data Mining”
  4. 4. Supervised Learning “Generalizing from Human-Intelligence”
  5. 5. “Generalizing”
  6. 6. Serving Personalized Ads
  7. 7. Recommendation Systems
  8. 8. Search Relevance Optimization
  9. 9. Sentiment Analysis
  10. 10. What is ML - Recap Two themes –Unsupervised Learning: “Data Mining” • Association rules, Clustering, ‘Text mining’ –Supervised Learning: Generalizing from Human-Intelligence • Ads, RecSys, Search Relevance, Sentiment Analysis
  11. 11. Developing ML/data-products (it helps to have collected data)
  12. 12. Big Data enables ML
  13. 13. Thinking Statistically
  14. 14. Visualization
  15. 15. Communicating data/results
  16. 16. Rigor/Ethics
  17. 17. “Setting expectations”
  18. 18. Developing ML/data-products - Recap Skills/Concerns •Collecting data •Statistical Thinking •Communication •Visualization •Ethics/Rigor •Setting expectations •Probabilistic “error-rate”
  19. 19. Q&A Discussion

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