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Azure Machine Learning

MSBIP møde nr. 25 - Azure ML

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Azure Machine Learning

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

About me

David Bojsen [email protected]

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

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

Machine Learning Algorithms

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Fixed set of algoritms (somewhat outdated)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)

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

DEMOBuilding an experiment to test/train/select a model

Building an experiment to publish a model

Testing model manually

Consuming a model from Power Query

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

Azure Stream Analytics

Azure Data Factory

Internet Of Things

Data

”Things”

”Devices”

ISS Agent

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/