Azure Machine Learning provides enterprise-class machine learning and data mining to the cloud. This presenter will cover 1) what AzureML is, 2) technical overview of AzureML for application development, 3) a reminder to consider SQL Server Data Mining, and 4) a recommend path for resources and next steps.

1. .NET Development with Azure Machine Learning (AzureML)
Mark Tabladillo PhD (Microsoft MVP, SAS Expert)
Consultant SolidQ
Seattle Business Intelligence –November 24, 2014

2. Entertainment: Pacman1981 in 2014
https://www.youtube.com/watch?v=flfE-cX8qjM

3. Meet your neighbors

4. Mark Tab
SQL Server MVP; SAS Expert
Consulting
Training
Teaching
Presenting
Linked In
@MarkTabNet

5. What is Azure ML?

6. Machine Learning / Predictive Analytics
Vision Analytics
Recommenda-tion engines
Advertising analysis
Weather forecasting for business planning
Social network analysis
Legal discovery and document archiving
Pricing analysis
Fraud detection
Churn analysis
Equipment monitoring
Location-based tracking and services
Personalized Insurance
Machine learning & predictive analytics are core capabilities that are needed throughout your business

7. Microsoft Azure ML Intro
https://www.youtube.com/watch?v=SJtNJepz-pM
https://www.youtube.com/watch?v=6IEx9G8RwP4

8. Microsoft Azure Machine Learning
Microsoft Azure Machine Learning, a fully-managed cloud service for building predictive analytics solutions, helps overcome the challenges most businesses have in deploying and using machine learning.
How? By delivering a comprehensive machine learning service that has all the benefits of the cloud.
Azure Ml brings together the capabilities of new analytics tools, powerful algorithms developed for Microsoft products like Xbox and Bing, and years of machine learning experience into one simple and easy-to-use cloud service.

9. How could data science apply?
Let’s look at three companies

10. Telecommunications

11. Oil and Gas

12. Volkswagen Group

14. What
Why
How
Relational Data Warehouse
Store data in table; query faster; handles lots of transactions
Dimensionalmodels; optimized reads; indexing
Hadoop & HDInsight
Storelarge amounts of data; unstructured data, flexible schemas
Distributedcomputing; virtualization
Tabular
Fastad-hoc, flexible
In-memory
MultidimensionalOLAP
Aggregations
Storeaggregations; semanticmodel
Data Mining & Machine Learning
Predictions, descriptions,prescriptions
Estimations; Query the model

16. Demos: Technical Overview of AzureML
Empirical Technical Description

17. The Power of Cloud Machine Learning
https://www.youtube.com/watch?v=z-lsheCYtug

18. Integration with R
•Data scientists can bring their existing assets in R and integrate them seamlessly into their Azure ML workflows.
•Using Azure ML Studio, R scripts can be operationalized as scalable, low latency web services on Azure in a matter of minutes!
•Data scientists have access to over 400 of the most popular CRAN packages, pre-installed. Additionally, they have access to optimized linear algebra kernels that are part of the Intel Math Kernel Library.
•Data scientists can visualize their data using R plotting libraries such as ggplot2.
•The platform and runtime environment automatically recognize and provide extensibility via high fidelity bi-directional dataframeand schema bridges, for interoperability.
•Developers can access common ML algorithms from R and compose them with other algorithms provided by the Azure ML platform. http://blogs.technet.com/b/machinelearning/archive/2014/09/17/ extensibility-and-r-support-in-the-azure-ml-platform.aspx

19. Blog
http://blogs.technet.com/b/francesco_diaz/archive/2014/08/30/using-language-r- and-azure-machine-learning-to-load-data-from-azure-sql-database.aspx

20. Applications Development

21. SQL Server Data Mining: Analysis Services
http://sqlserverdatamining.com

22. Data mining add-in for business analysts
•Ease of use
•Rich data mining
•Scalable

23. Split Personality of SSAS
SS
SQL
AS
NoSQL

24. Data platform: SQL Server 2014
Database Services
SQL Server* SQL Azure*
ReplicationSQL Azure Data Sync*
Full Text & Semantic Search*
Data Integration Services
Integration Services*
Master Data Services*
Data Quality Services*
StreamInsight* Project “Austin”*
Analytical Services
Analysis Services*
Data Mining
PowerPivot*
Reporting Services
Reporting Services* SQL Azure Reporting*
Report Builder
Power View*

25. What Enterprise Tools support SSAS?
Data Mining
SSMS
SSIS
PowerShell

26. SSAS Logical Architecture

27. SSAS Physical Architecture

28. Project Samples
http://sqlserverdatamining.com

29. Path for Next Steps

30. People

31. Difference in Proportions Test
Lexicon Based Sentiment Analysis
Forecasting-Exponential Smoothing
Forecasting -ETS+STL
Forecasting-AutoRegressiveIntegrated Moving Average (ARIMA)
Normal Distribution QuantileCalculator
Normal Distribution Probability Calculator
Normal Distribution Generator
Binomial Distribution Probability Calculator
Binomial Distribution QuantileCalculator
Binomial Distribution Generator
Multivariate Linear Regression
Survival Analysis
Binary Classifier
Cluster Modeldatamarket.azure.com

32. Codeplex Project for AzureML
http://azuremlexcel.codeplex.com/

33. Data Market: Sell Your Work
https://datamarket.azure.com/browse?query=machine+learning
https://datamarket.azure.com/dataset/aml_labs/anomalydetection

34. Free Tier: AzureML

35. Free Tier: AzureML

36. MarkTab Analysis for Gigaomhttp://research.gigaom.com/report/sector-roadmap-machine-learning-and-predictive-analytics/

37. Software
Dreamspark(students); BizSpark(businesses)
SQL Server 2014 Enterprise (includes database engine, Analysis Services, SSMS and SSDT)
http://www.microsoft.com/en-us/server-cloud/products/sql-server/default.aspx
Microsoft Office
http://office.microsoft.com/en-us/
Primer on Power BI --MarkTab
http://blogs.msdn.com/b/mvpawardprogram/archive/2014/08/04/primer-on-power-bi-business- intelligence.aspx

38. Resources
Machine Learning Blog http://blogs.technet.com/b/machinelearning/
Forum http://social.msdn.microsoft.com/forums/azure/en- US/home?forum=MachineLearning
SQL Server Data Mining http://sqlserverdatamining.com
MarkTab http://marktab.net

39. Organizations
Professional Association for SQL Server http://www.sqlpass.org
PASS Business Analytics Conference http://www.passbaconference.com

40. PASS Data Science (virtual chapter)

41. Data
Go Get It

44. Abstract
Azure Machine Learning provides enterprise-class machine learning and data mining to the cloud. This presenter will cover 1) what AzureML is, 2) technical overview of AzureML for application development, 3) a reminder to consider SQL Server Data Mining, and 4) a recommend path for resources and next steps.