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Machine Learning Intro for Anyone and Everyone


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A fun and math free introduction to Machine Learning. It provides a step to step approach for everyone to get started with Machine Learning using Microsoft Azure ML

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Machine Learning Intro for Anyone and Everyone

  1. 1. 1 Machine Learning For Everyone We Will be starting soon
  2. 2. Agenda Introductions 1) What is Machine Learning 2) Machine Learning Concepts Big Data Trunk Services 3) Machine Learning Real life example ◦ We will solve together 4) Azure ML Demo ◦ ◦ Azure ML Overview 2
  3. 3. Introduction ØRaju Shreewastava ØCo-Founder ØData & Analytics all my life ØArchitect by Profession, Artist at heart, Teacher in Soul ØHelp people in the Big Data Revolution 3
  4. 4. AUTHOR Sams Publication Big Data on Azure 4
  5. 5. Highlights oHeadquartered in Bay Area, California o Offshore Development Center in India o Practice Areas o Big Data and Data Science o Business Intelligences & Analytics o Data Warehouses o IOT (Internet of Things) o Cloud (Azure/AWS) oProducts oTraining Services (Individual & Corporate) oE -Verified 5 Technology Partners
  6. 6. Machine Learning Concepts 6
  7. 7. What is Machine Learning 7
  8. 8. ML vs Traditional Programming 8
  9. 9. Machine Learning Example 9
  10. 10. ML Use cases 10 • Weather forecasting. • E-commerce. • Self-driving cars. • Hazards of new medicine. • Space research. • Fraud detection. • Stock trade analysis. • Business forecasting. • Social networks. • Customers likelihood.
  11. 11. 11 Gartner Hype Cycle For Emerging Technology Jul 2016
  12. 12. Machine Learning Offerings 12 Amazon Machine Learning Google TensorFlow Machine Learning Microsoft Azure Machine Learning Spark Machine Learning
  13. 13. 13 Supervised Learning (Train Data) Unsupervised Learning (No Train Data) RED GREEN
  14. 14. Supervised Vs UnSupervised Learning SUPERVISED LEARNING: suppose the fruits are apple,banana,cherry,grape. so you already know from your previous work that, the shape of each and every fruit so it is easy to arrange the same type of fruits at one place. here your previous work is called as train data in data mining. This type of data you will get from the train data. This type of learning is called as supervised learning. E. g. Classification and Regression UNSUPERVISED LEARNING: RED COLOR GROUP: apples & cherry fruits. GREEN COLOR GROUP: bananas & grapes. so now you will take another physical character as size, so now the groups will be some thing like this. RED COLOR AND BIG SIZE: apple. RED COLOR AND SMALL SIZE: cherry fruits. GREEN COLOR AND BIG SIZE: bananas. GREEN COLOR AND SMALL SIZE: grapes. here you didn't know learn any thing before means no train data and noresponse variable. E.g. Clustering 14
  15. 15. Main Machine Learning Techniques 15 Classification Clustering Regression
  16. 16. Classification 16
  17. 17. Clustering 17
  18. 18. Regression Child’s Weight Prediction 18
  19. 19. Learning Techniques 19
  20. 20. Big Data Trunk ML Project 20
  21. 21. Real Life Project : Customer Retention Predictive Analytics Unhappy Customer Versus Engaged Customer
  22. 22. 22
  23. 23. Customer Info service Retention Score service …. Web service Engagement Meter INTERFACE Customer Info Dashboard Action Recommendation Engine (FI Managed) Customer Engagement Analytics Predictive Analytics/ Machine Learning PROCESSCOLLECTSOURCE FI Admin Portal/Branch LEARN Call Center User Online/Mobile
  24. 24. 10/7/17 NCR CONFIDENTIAL 24 (Under the Hood) Additional considerations 1) Customer Database 2) Explorative Analysis 3) Survival Model 4) Life time value
  25. 25. 25
  26. 26. ML Azure Demo 26
  27. 27. Contact Us 27
  28. 28. Big Data & Data Science 2 Days Workshop 28 Program DATE TIME Agenda Day 1 29-OCT-2017 Sun 10 AM to 4:00 PM PST (Classroom Santa Clara CA) Big Data – Apache Spark Day 2 5-NOV-2017 Sun 10 AM to 4:00 PM PST (Classroom Santa Clara CA) Machine Learning R Programming No Pre-Reqs Cost – Only $250
  29. 29. Free 4 hrs Bootcamp for your Company Corporate training § We provide Corporate trainings § Free 4 hrs Bootcamp for your company §Custom trainings can be provided for your companies need 29
  30. 30. Hire from us Paid or Unpaid Intern § Min 3 months § Win-Win Situation § Resources trained on Full Big data stack § Custom trainings can be provided for your companies need Resource Requirement § Get experienced professionals § Hire Part-time or Advisory Services 30
  31. 31. Contact Us Visit Website For any questions you can reach us at Phone– 510 -894-9922 Email 31
  32. 32. Thank you 32