What does Bob really want? Building recommendation systems based on cloud technologies Machine Learning or Data Science are one of today's hottest buzzwords. The scenarios in which Machine Learning can be applied are diverse and can range from predicting football scores to personalised recommendations in online shops to predictive maintenance in manufacturing. In this session I will present Azure Machine Learning - a service in Microsoft Azure that anyone can use to build predictive models using the provided machine learning algorithms and deploy it as a web service. Here, I will go through various options on how to use AzureML when going beyond just finding the products in retail that are in high demand: predicting the taste and preferences of customers (old and new) and giving appropriate recommendations.

1. What does Bob really want?
Building recommendation systems
based on cloud technologies
Olivia Klose | Technical Evangelist, Microsoft
NoSQL Usergroup Cologne, July 1st 2015

8. 13.06.20
15
SQLSaturday Rheinland
2015

10. The challenge in automation is
enabling computers to interpret
endless variation in handwriting.

11. The challenge in automation is
enabling computers to interpret
endless variation in handwriting.

14. 1. Too complex: When you can’t code it.
2. Too much: When you can’t scale it.
3. Too specialised: When you have to dapt/personalise.
4. Autonomous: When you can’t track it.

15. VALUE
DIFFICULTY
What
happened?
Why did
it happen?
What will
happen?
How can we
make it happen?
Traditional BI Advanced Analytics

16. Challenges
Skilled
Data Scientists Infrastructure
Time Scalable

19. ?

20. [green]
[sour]
[citrus]
[green]
[sweet]

22. Azure Machine Learning
Make machine learning accessible to every
enterprise, data scientist, developer,
information worker, consumer, and device
anywhere in the world.

23. ML
Studio
M
HDInsight
SQL Server VM
SQL DB
Blobs & Tabellen
Cloud
Desktopdateien
Exceltabelle
Andere…
Local
IDE for ML Web Service
MonetiseStorage Account

37. http://aka.ms/AzureML-Market

40. http://aka.ms/MLCheatSheet

41. In limited preview
SELECT text, sentiment(text)
FROM myStream
http://aka.ms/stream-ml

42. http://aka.ms/MLbook

43. aka.ms/azurenow
Machine Learning Series
http://aka.ms/MLserie
http://aka.ms/AzureML-resources
Machine Learning Cheat Sheet
http://aka.ms/MLCheatSheet
Machine Learning Studio
http://studio.azureml.net
Kostenloses E-Book
http://aka.ms/MLbook
oliviaklose.com
aka.ms/MLblog
@oliviaklose

44. © 2015 Microsoft Corporation.
All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks in the U.S. and/or other countries.
Olivia Klose
Technical Evangelist
Microsoft Deutschland GmbH
E-Mail: olivia.klose@microsoft.com
Blog: oliviaklose.com
Twitter: @oliviaklose