Download - Microsoft Azure Machine Learning

Microsoft Ignite 2015

2015 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9/3/2015 5:27 PM

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A Journey into Azure Machine Learning with R

Leila Etaati

M234

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Who Am I ?

Leila Etaati

Data Mining and BI Consultant

Speakers in Many Microsoft SQL Server Conferences (SQL Rally, Code camp and SQL Saturday )

10 Years experiences in SQL Server

Co-Lead Auckland BI User Group

PhD in Information System Department, Business School University of Auckland

Lecturer and Tutor of BI and database

@leila_etaati

[email protected]



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Agenda

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Introduction to Machine Learning

What is Azure ML

Azure ML Demos

Azure ML with R

Facts about Azure ML

Introduction to Machine Learning

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I believe over the next decade computing will become even more ubiquitous and intelligence will become ambient this will be made possible by an ever growing network of connected devices, incredible computing capacity from the cloud, insights from big data, and intelligence from machine learning.



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If you invent a breakthrough in Artificial Intelligence, so machines can learn, that is worth 10 Microsoft



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What is Machine Learning ?

The goal of machine learning is to build

computer systems that can

adapt and learn from their experience.

-Tom Dietterich



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Information Optimization

Value

Difficulty

What

Happened ?

Descriptive

Analytics

Diagnostic

Analytics

Predictive

Analytics

Prescriptive

Analytics

Why did it

Happen?

What Will

Happen?

How can we

Make it Happen?

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Mortgage

Applications

Pattern

Recognition

Health

Insurance

Fraud

Detection

Airline

Flights

Web Search

Page result

Example of Using Machine Learning

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Example of Using Machine Learning

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Microsoft Speech Recognition Control

Microsoft Search Engine

Microsoft Xbox and Kinect

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Machine Learning

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Should I used Machine Learning

Predication is Small

part of experiences

No Past data

Many Rules govern

Experience

Automated Predication is Core

Lots of History

Magic numbers in current prediction system

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Machine Learning Concepts

Data

Model

Parameters

Learning

Prediction

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Steps

First-Understand the Business Domain

Second-Understand the Business Problem

Third- What is the Right Data, Right

Column and Right Algorithm

Last-Combine Knowledge With

Machine Learning

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Steps to Build a Machin Learning

De/Refine

Business Rule

Sales More

Find Fraud

Find Potential Customers

Collect and Clean

Data

ETL Process

Split Data

Train Model

Test Model

Performance

Score Model

What type of Data

% for

Training

Choose Model

% for

Testing

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Evaluate

Models

De/Refine

Business Rule

Collect and Clean

Data

Split Data

Choose the Best Model

Model A

Model B

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What is Azure ML

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Data

scientist

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Microsoft Azure Machine Learning

Reduced Complexity

Access Through Web Browser, no need to install any thing

Collaborate work with anyone

Visual composition, easy to use, No Coding

Good storage of Algorithm (Use in Bing search, Xbox..)

Have good support for R studio, Python and Jupyter notebook

Load Data From Different Location

Clean data

Machine

Learning

Algorithms

R and

Python Language

Web services

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Cortana Analytics Suite successful experience with Azure MLhttps://www.youtube.com/watch?v=YxmAEMmwXYU

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Azure ML Demoes

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Demo: Azure ML Environment

Leila Etaati



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Demo:Classification Problem Example

Leila Etaati

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Titanic Classification Algorithm

Survived or Not

Titanic sank on15April 1912 after colliding with an iceberg

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Azure ML using R code

Leila Etaati



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Demo: Azure ML with R

Leila Etaati

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Fact about Azure ML

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Azure ML Algorithm

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Regression Algorithm

Classification

Algorithm

Discrete

Variables

Customer Preferences

Martial Status

Married, Divorce, Single

Income

More than 50K or

Less Than 50K

Continues

Variables

Income, Sales, Profit

Match Data Type

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Clustering Algorithm


Classification

Algorithm

Descriptive

Analysis

Predictive

Analysis

Predictive

Analysis

Descriptive and Predictive Analysis

1-Which other customers have similar preferences to this one?

2-What are the most common patterns in gasoline price changes?

1-When will this customer make another purchase?

2-How many new followers will I get next week?

1-Will this customer click on the top link?

2-Which offer should this customer receive?

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8.19999999999999933.21.41.2Sales1st Qtr2nd Qtr3rd Qtr4th Qtr

Clustering Algorithm


Classification

Algorithm

Supervised

Learning

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SSAS vs Azure ML

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SSAS Vs Azure ML

FeaturesUsabilityCostSupportEnd to end ProductCanned algorithmNot possible to change algorithmDMX CodeMore Visual Excel VersionIts not easy to startAll users can useIf you purchase SQL Sever: FreeFew books and small online community

Current and up to date algorithmIntegration with R and PythonCloud baseREST formatHard to interpret Drag and Drop UICustomize the AlgorithmFree version, limited optionsMore online Community

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Azure ML Pricing

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Questions

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Related Ignite NZ Sessions

Using Azure Machine Learning to predict Trade Me auction prices Ballroom 1 (Crowne Plaza)Wed 1:45pm

Windows 10 + Azure AD + Intune = full desktop management and provisioning in the cloud New Zealand 1 (SKYCITY)Fri 9:00am

Data Patterns for the Cloud Ballroom 1 (Crowne Plaza) Wed 10:40am

Azure Machine Learning: From Design to Integration Marlborough (SKYCITY) Fri 10:40am

Find me later at

Hub Happy Hour Wed 5:30-6:30pm

Hub Happy Hour Thu 5:30-6:30pm

Closing drinks Fri 3:00-4:30pm

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2

3

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Resources

TechNet & MSDN Flash

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http://aka.ms/technetnz http://aka.ms/msdnnz

http://aka.ms/ch9nz

Microsoft Virtual Academy

Free Online Learning

http://aka.ms/mva

Sessions on Demand

2014 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9/3/2015

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Complete your

session evaluation

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41

9/3/2015 5:27 PM

2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

2015 Microsoft Corporation. All rights reserved.

Microsoft, Windows and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9/3/2015 5:27 PM

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Download - Microsoft Azure Machine Learning

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