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Amazon Machine Learning for Developers

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Amazon Machine Learning is a service that makes it easy for developers of all skill levels to use machine learning technology. Amazon Machine Learning provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology. Once your models are ready, Amazon Machine Learning makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure. More information: https://aws.amazon.com/machine-learning/

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Amazon Machine Learning for Developers

  1. 1. AMAZON ML Machine Learning for developers Carlos Conde – @caarlco
  2. 2. PERSONALIZE
  3. 3. UNDERSTAND YOUR CUSTOMER Who is my customer really? What does he really like? What is happening with my products? Where do people consume my product?
  4. 4. THREE TYPES OF DATA-DRIVEN ANALYSIS Retrospective analysis and reporting Here-and-now real-time processing and dashboards Predictions to enable smart applications
  5. 5. MACHINE LEARNING Technology that automatically finds patterns in your data and uses them to make predictions for new data points
  6. 6. Demo.
  7. 7. MACHINE LEARNING IS EVERYWHERE
  8. 8. Amazon.com 1994
  9. 9. AMAZON MACHINE LEARNING Scalable & managed machine learning service
  10. 10. BEST PRACTICES & LESSONS LEARNED
  11. 11. USE ALL AVAILABLE DATA Your company has more data on your users than what you think…
  12. 12. Quizz What percentage of data do firms use for analytics? A: 12% C: 52% B: 34% D: 68%
  13. 13. Quizz What percentage of data do firms use for analytics? A: 12% C: 52% B: 34% D: 68%
  14. 14. ENRICH DATA BASED ON SOCIAL NETWORKS User’s friends are valuable sources of information
  15. 15. 75% of users select movies based on recommendations
  16. 16. HOMOPHILY People are friends with people like them.
  17. 17. ENRICH DATA BASED ON USER ENVIRONMENT User’s context heavily influences their behavior.
  18. 18. Geo-location data Device information Time of day and week Metadata from third parties …
  19. 19. ENRICH DATA BASED ON USER BEHAVIOR The way users interacts with the UI gives valuable information
  20. 20. THE MORE, THE BETTER (SOMETIMES) More data usually gives you better prediction accuracy.
  21. 21. MAKE NO PREMATURE ASSUMPTIONS We all have preconceived ideas about who are our users … Most often they are wrong.
  22. 22. GET CLOSER TO YOUR USERS Your customers live in the real world. Use IoT to bring your services closer.
  23. 23. Easy. Buy a copper tube ice maker kit
  24. 24. …And a shut-off valve…
  25. 25. …And a T-connector to tap the cold water supply line…
  26. 26. …And a hacksaw to cut the copper pipe…
  27. 27. …Finally, A special drill bit to make a hole in the kitchen floor for the copper tubing.
  28. 28. “It is not the strongest species that survive, nor the most intelligent, but the ones most responsive to change.”
  29. 29. @caarlco

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