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Would I have survived the Titanic?
Machine Learning in Microsoft Azure
SQL Saturday 409
Olivia Klose
Technical Evangelist,...
Organizer
SQLSaturday Rheinland 201513.06.2015
Bronze Sponsor
SQLSaturday Rheinland 201513.06.2015
Silver Sponsor
SQLSaturday Rheinland 201513.06.2015
Gold Sponsor
SQLSaturday Rheinland 201513.06.2015
You rock!
SQLSaturday Rheinland 201513.06.2015
Save the date!
13.06.2015 SQLSaturday Rheinland 2015
WHAT IS MACHINE LEARNING?
13.06.2015 SQLSaturday Rheinland 2015
Machine Learning – Where?
Machine Learning – Where?
13.06.2015 SQLSaturday Rheinland 2015
13.06.2015 SQLSaturday Rheinland 2015
13.06.2015 SQLSaturday Rheinland 2015
What is Machine Learning?
“The goal of machine learning is
to program computers
to use example data or past experience
to ...
What is Machine Learning?
Methods and Systems that...
adapt
predict new
data
optimise an
action
extract
information
summar...
What is Machine Learning not?
Methods and Systems that...
do „Garbage-In-
Knowledge-Out“
predict without
data modelling &
...
Machine Learning – Warum?
1. Too complex: When you can’t code it.
(e.g. Natural Language Processing, hand writing recognit...
Advanced Analytics Scenarios
13.06.2015 SQLSaturday Rheinland 2015
EXAMPLE SOLUTIONS
THE MACHINE LEARNING
PROCESS
13.06.2015 SQLSaturday Rheinland 2015
Machine Learning Process
Data
Clean
Transform
Maths
Build
Model
Predict
Hm – what?
𝑓 X = y
Input
Matrix/Table
Output
Vector/Column
Hm – what?
ℎ X = y
Input
Matrix/Table
Predicted Output
Vector/Column
Hypothesis
Data
13.06.2015 SQLSaturday Rheinland 2015
Forecast Temperature Windy Play tennis?
Sunny Low Yes Play
Sunny High Yes Don't...
Säubern, transformieren, Mathe
Forecast Temperature Windy Play tennis?
Sunny Very Low Yes Play
Sunny High Yes Don't Play
S...
Säubern, transformieren, Mathe
13.06.2015 SQLSaturday Rheinland 2015
[[ 1.000000],
[ -1.000000],
[ -1.000000],
[ 1.000000]...
Säubern, transformieren, Mathe
13.06.2015 SQLSaturday Rheinland 2015
[[ 1.000000, 0.000000, 1.000000],
[ 1.000000, 1.00000...
Modell Bauen
Forecast
Temperature WindyYes
Cloudy
Sunny
Low
Yes
Rainy
High
No
No
Yes
Yes
No
Forecast Temperature Windy Pla...
Vorhersagen
Forecast Temperature Windy Play?
Sunny Low No ?
Forecast
Temperature WindyYes
Cloudy
Sunny
Low
Yes
Rainy
High
...
Forecast
Temperature WindyYes
Cloudy
Sunny
Low
Yes
Rainy
High
No
No
Yes
Yes
No
Vorhersagen
Play!
Forecast Temperature Wind...
Popular Machine Learning Models
 Support Vector Machines
 Neural Networks
 Decision Trees
True Label
Positive Negative
PredictedLabel
Positive
True positive
(TP)
False positive
(FP)
𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 =
𝑡𝑝
𝑡𝑝 + 𝑓𝑝
Negativ...
True Label
Patient is sick. Patient is healthy.
PredictedLabel
Testpositive
Test correctly states that
the patient is sick...
AZURE MACHINE LEARNING
13.06.2015 SQLSaturday Rheinland 2015
Azure Machine Learning
Make machine learning accessible to
every enterprise, data scientist, developer,
information worker...
Azure Machine Learning
HDInsight
SQL Server VM
SQL DB
Blobs & Tables
Cloud
Desktop files
Excel
spreadsheets
Others…
Lokal
...
13.06.2015 SQLSaturday Rheinland 2015
DEMO
Surviving on the Titanic
SO DO I NEED TO LEARN
MACHINE LEARNING NOW?
13.06.2015 SQLSaturday Rheinland 2015
DEMO
Azure ML Marketplace
WHAT DID WE DO?
13.06.2015 SQLSaturday Rheinland 2015
13.06.2015 SQLSaturday Rheinland 2015
http://aka.ms/MLCheatSheet
Stream Analytics + Machine Learning
In limited preview
13.06.2015 SQLSaturday Rheinland 2015
SELECT text, sentiment(text)
...
Free E-Book
http://aka.ms/MLbook
Blog-Series on Machine Learning
http://aka.ms/MLSerie
http://aka.ms/AzureML-Ueberblick
http://aka.ms/AzureML-resources
Free Video Series on Azure ML
http://aka.ms/AzureML-MVA
Further Information
13.06.2015 SQLSaturday Rheinland 2015
aka.ms/azurenow
Machine Learning Series
http://aka.ms/MLserie
ht...
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Would I have survived the Titanic? Machine Learning in Microsoft Azure

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 an end-to-end workflow in which I will predict the survival chances on the Titanic.

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Would I have survived the Titanic? Machine Learning in Microsoft Azure

  1. 1. Would I have survived the Titanic? Machine Learning in Microsoft Azure SQL Saturday 409 Olivia Klose Technical Evangelist, Microsoft @oliviaklose | http://oliviaklose.com
  2. 2. Organizer SQLSaturday Rheinland 201513.06.2015
  3. 3. Bronze Sponsor SQLSaturday Rheinland 201513.06.2015
  4. 4. Silver Sponsor SQLSaturday Rheinland 201513.06.2015
  5. 5. Gold Sponsor SQLSaturday Rheinland 201513.06.2015
  6. 6. You rock! SQLSaturday Rheinland 201513.06.2015
  7. 7. Save the date! 13.06.2015 SQLSaturday Rheinland 2015
  8. 8. WHAT IS MACHINE LEARNING? 13.06.2015 SQLSaturday Rheinland 2015
  9. 9. Machine Learning – Where?
  10. 10. Machine Learning – Where?
  11. 11. 13.06.2015 SQLSaturday Rheinland 2015
  12. 12. 13.06.2015 SQLSaturday Rheinland 2015
  13. 13. 13.06.2015 SQLSaturday Rheinland 2015
  14. 14. What is Machine Learning? “The goal of machine learning is to program computers to use example data or past experience to solve a given problem.” Introduction to Machine Learning, 2nd Edition, MIT Press
  15. 15. What is Machine Learning? Methods and Systems that... adapt predict new data optimise an action extract information summarise data
  16. 16. What is Machine Learning not? Methods and Systems that... do „Garbage-In- Knowledge-Out“ predict without data modelling & feature engineering are always perfect replace business rules
  17. 17. Machine Learning – Warum? 1. Too complex: When you can’t code it. (e.g. Natural Language Processing, hand writing recognition, Computer Vision,…) 2. Too much: When you can’t scale it. (e.g. Spam & fraud detection, healthcare) 3. Too specialised: When you have to adapt/personalise. (e.g. Amazon, Netflix) 4. Autonomous: When you can’t track it. (e.g. AI gaming, robotics)
  18. 18. Advanced Analytics Scenarios 13.06.2015 SQLSaturday Rheinland 2015 EXAMPLE SOLUTIONS
  19. 19. THE MACHINE LEARNING PROCESS 13.06.2015 SQLSaturday Rheinland 2015
  20. 20. Machine Learning Process Data Clean Transform Maths Build Model Predict
  21. 21. Hm – what? 𝑓 X = y Input Matrix/Table Output Vector/Column
  22. 22. Hm – what? ℎ X = y Input Matrix/Table Predicted Output Vector/Column Hypothesis
  23. 23. Data 13.06.2015 SQLSaturday Rheinland 2015 Forecast Temperature Windy Play tennis? Sunny Low Yes Play Sunny High Yes Don't Play Sunny High No Don't Play Cloudy Low Yes Play Cloudy High No Play Cloudy Low No Play Rainy Low Yes Don't Play Rainy Low No Play Sunny Low No ? 𝑓 x = 𝑦 Features / Input: (Forecast, Temperature, Windy) e.g. x = sunny, low, yes Play / Don‘t Play
  24. 24. Säubern, transformieren, Mathe Forecast Temperature Windy Play tennis? Sunny Very Low Yes Play Sunny High Yes Don't Play Sunny High Kinda Don't Play Cloudy ? Yes One place Fleecy clouds High No Play Cloudy Low No Play Rainy ? Yes Don't Play Rainy Low No Play Sunny Low No ?
  25. 25. Säubern, transformieren, Mathe 13.06.2015 SQLSaturday Rheinland 2015 [[ 1.000000], [ -1.000000], [ -1.000000], [ 1.000000], [ 1.000000], [ 1.000000], [ -1.000000], [ 1.000000]] Forecast Temperature Windy Play tennis? Sunny Low Yes Play Sunny High Yes Don't Play Sunny High No Don't Play Cloudy Low Yes Play Cloudy High No Play Cloudy Low No Play Rainy Low Yes Don't Play Rainy Low No Play Sunny Low No ?
  26. 26. Säubern, transformieren, Mathe 13.06.2015 SQLSaturday Rheinland 2015 [[ 1.000000, 0.000000, 1.000000], [ 1.000000, 1.000000, 1.000000], [ 1.000000, 1.000000, -1.000000], [ 2.000000, 0.000000, 1.000000], [ 2.000000, 1.000000, -1.000000], [ 2.000000, 0.000000, -1.000000], [ 3.000000, 0.000000, 1.000000], [ 3.000000, 0.000000, -1.000000]] Forecast Temperature Windy Play tennis? Sunny Low Yes Play Sunny High Yes Don't Play Sunny High No Don't Play Cloudy Low Yes Play Cloudy High No Play Cloudy Low No Play Rainy Low Yes Don't Play Rainy Low No Play Sunny Low No ?
  27. 27. Modell Bauen Forecast Temperature WindyYes Cloudy Sunny Low Yes Rainy High No No Yes Yes No Forecast Temperature Windy Play tennis? Sunny Low Yes Play Sunny High Yes Don't Play Sunny High No Don't Play Cloudy Low Yes Play Cloudy High No Play Cloudy Low No Play Rainy Low Yes Don't Play Rainy Low No Play Sunny Low No ?
  28. 28. Vorhersagen Forecast Temperature Windy Play? Sunny Low No ? Forecast Temperature WindyYes Cloudy Sunny Low Yes Rainy High No No Yes Yes No
  29. 29. Forecast Temperature WindyYes Cloudy Sunny Low Yes Rainy High No No Yes Yes No Vorhersagen Play! Forecast Temperature Windy Play? Sunny Low No ?
  30. 30. Popular Machine Learning Models  Support Vector Machines  Neural Networks  Decision Trees
  31. 31. True Label Positive Negative PredictedLabel Positive True positive (TP) False positive (FP) 𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 = 𝑡𝑝 𝑡𝑝 + 𝑓𝑝 Negative False negative (FN) True negative (TN) 𝑅𝑒𝑐𝑎𝑙𝑙 = 𝑡𝑝 𝑡𝑝 + 𝑓𝑛 𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦 = 𝑡𝑝 + 𝑡𝑛 𝑡𝑝 + 𝑡𝑛 + 𝑓𝑝 + 𝑓𝑛 Is the model any good? Confusion Matrix 13.06.2015 SQLSaturday Rheinland 2015
  32. 32. True Label Patient is sick. Patient is healthy. PredictedLabel Testpositive Test correctly states that the patient is sick. Test incorrectly states that the patient is sick (although he/she is healthy). 𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 = 𝑡𝑝 𝑡𝑝 + 𝑓𝑝 Testnegative Test incorrectly states that the patient is healthy (although being sick). Test correctly states that the patient is healthy. 𝑅𝑒𝑐𝑎𝑙𝑙 = 𝑡𝑝 𝑡𝑝 + 𝑓𝑛 𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦 = 𝑡𝑝 + 𝑡𝑛 𝑡𝑝 + 𝑡𝑛 + 𝑓𝑝 + 𝑓𝑛 Is the model any good? Confusion Matrix 13.06.2015 SQLSaturday Rheinland 2015
  33. 33. AZURE MACHINE LEARNING 13.06.2015 SQLSaturday Rheinland 2015
  34. 34. Azure Machine Learning Make machine learning accessible to every enterprise, data scientist, developer, information worker, consumer, and device anywhere in the world.
  35. 35. Azure Machine Learning HDInsight SQL Server VM SQL DB Blobs & Tables Cloud Desktop files Excel spreadsheets Others… Lokal ML Studio IDE for ML Web Service M Monetise Storage Account
  36. 36. 13.06.2015 SQLSaturday Rheinland 2015 DEMO Surviving on the Titanic
  37. 37. SO DO I NEED TO LEARN MACHINE LEARNING NOW? 13.06.2015 SQLSaturday Rheinland 2015 DEMO Azure ML Marketplace
  38. 38. WHAT DID WE DO? 13.06.2015 SQLSaturday Rheinland 2015
  39. 39. 13.06.2015 SQLSaturday Rheinland 2015 http://aka.ms/MLCheatSheet
  40. 40. Stream Analytics + Machine Learning In limited preview 13.06.2015 SQLSaturday Rheinland 2015 SELECT text, sentiment(text) FROM myStream http://aka.ms/stream-ml
  41. 41. Free E-Book http://aka.ms/MLbook
  42. 42. Blog-Series on Machine Learning http://aka.ms/MLSerie http://aka.ms/AzureML-Ueberblick http://aka.ms/AzureML-resources
  43. 43. Free Video Series on Azure ML http://aka.ms/AzureML-MVA
  44. 44. Further Information 13.06.2015 SQLSaturday Rheinland 2015 aka.ms/azurenow Machine Learning Series http://aka.ms/MLserie http://aka.ms/AzureML-Ueberblick http://aka.ms/AzureML-resources Machine Learning Video-Series (MVA) http://aka.ms/AzureML-MVA Machine Learning Studio http://studio.azureml.net Free E-Book http://aka.ms/MLbook oliviaklose.com aka.ms/MLblog @oliviaklose

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