Presentation about Azure ML for the Danish MSBIP user group

1. Azure Machine
Learning

2. Agenda
About me
Introduction to Azure Machine Learning
Differences between Azure ML and SSAS Data Mining
Demo
• Azure ML
• Consume ML Webservice from Power Query
Quick intro to other relevant tools in Azure

3. About me
David Bojsen dlb@kapacity.dk
36 years old, married, 2 children (7 and 17)
8 years of experience with SQL Server and Microsoft BI
11 years of experience with C# and .NET
BI Manager at TELMORE since April 2009
Senior Business Analytics Architect at Kapacity since April 2013
BI Developer – NOT data scientist

4. Introduction to Azure Machine Learning
Azure Cloud Service
Prebuilt standard models for data discovery and prediction (unsupervised
learning or supervised learning)
Framework for building new and/or selling models
Allow you to build a model using R or/and standard algorithms
About finding an algorithm/model for determining an outcome (well-defined
problem – e.g. given a set of features what is the probability of x, what is the
predicted price of selling a house, what classification does an ”entity” belong
to)
Trained AND scored based on a dataset
Inputs is a predefined set of features that can be used to predict an outcome

5. Machine Learning Algorithms

6. Azure ML vs. SSAS Data Mining
Azure ML
Pay as you Go
Fixed set of algorithms
extensible by using R
Easy visual interface
Cloud (first)
Batch / online requests
SSAS Data Mining
Free (With SQL Server)
Fixed set of algoritms
(somewhat outdated)
Integrated in Visual Studio
On-premise
Batch requests
Good for data discovery (thru
Excel add-in)

7. Extensability
R
• Access to over 400 of the most popular CRAN packages
• Your own custom code
Python
• Python Tools for Visual Studio
(Check Azure ML Blog)
• Not yet integrated in ML Studio

8. DEMO
Building an experiment to test/train/select a model
Building an experiment to publish a model
Testing model manually
Consuming a model from Power Query

9. Other relevant services in Azure
Azure Stream Analytics
• Think Stream Insight In The Cloud
Azure Data Factory
• Think Integration Services In The Cloud (for cloud and on-prem)
Azure Service Bus
Azure Event Hubs
Azure Intelligent Systems Service
• All related to Internet Of Things

10. Azure Stream Analytics

11. Azure Data Factory

12. Internet Of Things
Data
”Things”
”Devices”
ISS Agent

13. Want to know more?
• Azure Machine Learning
• Service - http://azure.com/ML
• Documentation – http://aka.ms/MLDS
• Pricing – http://aka.ms/MLPricing
• Studio – http://studio.azureml.com
• FAQ – http://aka.ms/MLFAQ
• MarketPlace – http://aka.ms/MLMarket
• Blog – http://aka.ms/MLBlog
• Azure Stream Analytics – http://azure.microsoft.com/en-us/services/stream-analytics/
• Azure Data Factory – http://azure.microsoft.com/en-us/services/data-factory/
• http://www.internetofyourthings.com/