Azure Machine Learning 101 slides which I used on Advanced Technology Days conference, held in Zagreb (Croatia) on November 12th and 13th. Slides are divided into 2 parts. First part is introducing machine learning in a simple way with some basic definitions and basic examples. Second part is introducing Azure Machine Learning service including main features and workflow. Slides are used only 30% of the presentation time so there is no much detailed information on them regarding machine learning. Rest of the time I did live demos on Azure Machine Learning portal which is probably more interesting to the audience. Presentation can be useful as a concept for similar topics or to combine it some other resource. If you need access to the demos just send me a message so I will grant you access to Azure ML workspace where are all experiments used in this session.

2. Azure Machine Learning 101,
Renato Jović
Senior Software Developer | Tagit Solutions Inc.
renato@tagitinc.com

3. Agenda
MACHINE LEARNING
What and how? Types of ML? Examples of machine learning?
AZURE MACHINE LEARNING
Build ML models using Drag&Drop from your favorite browser. Too good to be true!
DEMO #1 –Breast cancer prediction(Basicintroduction)
DEMO #2 –Adultincomeprediction(API showcase)
DEMO #3 –Azure ML lovesR(R script integration)
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4. “A breakthrough in machine learning would be worth ten
Microsofts” -Bill Gates, Chairman, Microsoft
“Machine learning is the next Internet”-Tony Tether, former director, DARPA
“Machine learning is the hot new thing” -John Hennessy, President, Stanford
“Web rankings today are mostly a matter of machine learning”
PrabhakarRaghavan, former Dir. Research, Yahoo
“Machine learning is going to result in a real revolution” –
Greg Papadopoulos, former CTO, Sun

5. What is Machine Learning?
Machine learningis a scientific discipline that deals with the construction and study of algorithms that can learn from data. Such algorithms operate by building a model based on inputs and using that to make predictions or decisions, rather than following only explicitly programmed instructions.
http://en.wikipedia.org/wiki/Machine_learning

6. What is Machine Learning?
http://dilbert.com/strips/comic/2013-02-02/

7. Machine learning –all aroundus
Stock market, temperature value predictions
Weather forecast
Web search and recomendations
Face (object) recognition systems

8. Machine learning process

9. Classes of learning
Classification
Binary classification –yes/no, 1/0, male/female
Multi-class classification –{A, B, C, D}, {1, 2}, {teacher, student}
Regression
Predict a real value –temperature, stock value...
Ranking
Order items by some criteria –web search
Clustering
Partition items into group –twitter posts

10. Machine Learning algorithms
Neural networks –supervised learning

11. Machine Learning algorithms
Decision trees –supervised learning

12. Machine Learning algorithms
Clustering –unsupervised learning

13. Azure machine learning

14. Azure Machine Learning
Newest Azure service which reduces complexity of Machine learning process and brings ML to broader audience
Possibility to develop and put intoproduction ML models without writing line of code.
Availabilityofmanytop of the classmachine learning algorithms (internally used at other Microsoft products)
Easy ML model deployment and usage using restful API
Easy collaboration on Azure Machine Learning projects
Support for open source framework R

15. Azure Machine Learning workspace

16. Azure ML workflow
•HDInsight
•SQL Server VM
•SQL DB
•Blobs & tables
•Local Files
Publish API in minutes
Devices Applications Dashboards
Data
Microsoft Azure Machine Learning
API
Storage space
Web
Microsoft Azure portal
Workspace
MLStudio
Business problem
Business value
Modeling
Deployment
•Desktop files
•Excel spreadsheet
•Other data files on PC
Cloud
Local
http://channel9.msdn.com/events/TechEd/Europe/2014/DBI-B218

17. DEMO time!
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18. Resourceshttp://en.wikipedia.org/wiki/Book:Machine_Learning_- _The_Complete_Guide
http://blogs.technet.com/b/machinelearning/ http://azure.microsoft.com/en-us/documentation/services/machine- learning/
http://cran.r-project.org/doc/manuals/R-intro.pdf
https://archive.ics.uci.edu/ml/datasets.html

19. Q&A

20. Thank you!
Email: renato@tagitinc.com
Twitter: @rjovic