1. Make Predictions Using Azure Machine Learning Studio
Amit Rappel

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4. Who am I? Amit Rappel 35 years old Kfar Saba Married + 1
2000 – Electrical engineering & Technion
2005 – System IAF
2008 – 2014 Goji
2015 – now Data scientist & Naya
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5. Recommender system using Azure ML Studio
Agenda 4
Recommender system using Azure ML Studio 1
Data science 2
Recommender systems 3
Azure ML
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6. Chapter 1
Data science

7. What is data science – 1 of 3
Model
Features
Predictions

8. What is data science – 2 of 3
Model
Features
Data
Problem type
Model
New data
Prediction

9. What is data science – 3 of 3
Problem
Good-work sign
Job security...
ETL
Pre-processing
Train-test split
Deploy
Data
Visualize
Fitting
Train-test split
Features
Building
Testing
Assessment
Overfitting
Relevancy
Validate

10. FAQ What’s necessary for doing data science?
Math & statistics
Hacking skills (programming)
Substantive expertise (business)
What’s the relation with big data?
Data science and big data are independent !!!
Big data refers to infrastructural problems
Data science can work in a big data environment

11. Applications Regression Classification Clustering Miscellaneous
Lifetime value (LTV)
Inventory management
Classification
Spam filter
Churn
Fraud detection
Clustering
Customer segmentation
Resources allocation
Miscellaneous
Anomaly detection
Web analytics
Sentiment analysis
Recommender systems…

12. Chapter 2
recommender systems

13. Concept
It is all about getting better conversion by showing the right item to the right user
Collect
Analyze
Recommend

14. Bottom line Target an active user Find neighbors Rank neighbors
Score recommendations
Recommend
Evaluate entire system

15. Example – the MovieLens dataset
ratings
movies
671 users, 9066 movies, ratings (~1.6%)

16. Getting dirty with Python (1 of 5)

17. Getting dirty with Python (2 of 5)

18. Getting dirty with Python (3 of 5)

19. Getting dirty with Python (4 of 5)

20. Getting dirty with Python (5 of 5)

21. Chapter 3
Azure Ml

22. Microsoft Azure
Microsoft Azure – cloud-computing service for building, creating, deploying and managing applications and services.
Web services
Azure ML – Azure framework for building and testing predictive analytics solutions.
Azure ML Studio

23. Recommender system using azure ml studio
Chapter 4
Recommender system using azure ml studio

24. Experiment overview

25. Q & A