Predicting the future as a service with Azure ML and R Barbara Fusinska@BasiaFusinska

About me

ProgrammerMachine Learning

Data Solutions Architect@BasiaFusinska

Agenda• Machine Learning

• Supervised vs unsupervised learning• Building blocks

• Azure ML• Classification/Regression processes• Training vs Testing• Building a solution• Using R code• Learning from the community

Machine Learning?

Movies GenresTitle # Kisses # Kicks Genre

Taken 3 47 Action

Love story 24 2 Romance

P.S. I love you 17 3 Romance

Rush hours 5 51 Action

Bad boys 7 42 Action

Question:What is the genre of Gone with the wind

?

Data-based classificationId Feature 1 Feature 2 Class

1. 3 47 A

2. 24 2 B

3. 17 3 B

4. 5 51 A

5. 7 42 A

Question:What is the class of the entry with the following

features:F1: 31, F2: 4

?

Data Visualization

0 5 10 15 20 25 30 35 40 450

10

20

30

40

50

60 Rule 1:If on the left side of the line then Class = A

Rule 2:If on the right side of the line then Class = B

A

B

Chick sexing

Supervised learning• Classification, regression• Label, target value• Training & Test sets

Unsupervised learning• Clustering, feature selection• Finding structure of data• Statistical values describing the data

Machine Learning workflowData

preparation Data split

Machine Learning algorithm

Trained model Score

Clean data

Training data Test data

Non-ML components• Data cleansing & transformation• Splitting data• I/O• Model evaluation• Comparing algorithms• Algorithms settings

Azure Machine Learning ServiceData -> Predictive model -> Operational web API in minutes

Blobs and TablesHadoop (HDInsight)Relational DB (Azure SQL DB)

Data Clients

Model is now a web service that is callable

Monetize the API through our marketplace

API

Integrated development environment for Machine Learning

ML STUDIO

Azure ML data sources• Built in datasets• Save datasets• Uploaded data• Import data module:• Web URL via HTTP• Hive Query• Azure SQL Database• Azure Table• Azure Blob Storage• Data Feed Provider

Demo: Income predictionSimple Machine Learning processUsing built in datasetsScoring & Evaluation

Machine Learning building blocks • Built-in components• Datasets• Algorithms• Scoring & Evaluation

• Binary classification• I/O• Visualization

Demo: Automobile price reductionData preparationTraining/Test splitWeb Service setup

Building a solution• Regression• Dataset upload• Data preparation• Training vs Testing• Web service

Demo: Credit risk assessmentSaved datasetAlgorithm comparisonUsing R

Comparing solutions• Reading data from external

source• Data normalisation• Using R scripts

Demo: Twitter sentiment analysisUploading templateFeature hashingFeature selection

Cortana Intelligence Gallery

Using Cortana gallery• Creating experiment from

template• Feature selection• Scoring & evaluation of training

and test data

Other Azure ML capabilities• History• Debugging• Parameters• Cross-validation• Retraining model• Feature selection

Thank you

BarbaraFusinska.com@BasiaFusinska