Vision Analytics

Recommenda-

tion engines

Advertising

analysis

Weather

forecasting for

business

planning

Social network

analysis

Legal

discovery and

document

archiving

Pricing analysis

Fraud

detection

Churn

analysis

Equipment

monitoring

Location-based

tracking and

services

Personalized

Insurance

Machine learning & predictive analytics are core capabilities that are needed throughout your business

• Automated prediction is

core

• Lots of past data already

available

• Magic numbers in current

prediction system

Yes

• Prediction is small part of

experience

• No past data available

• Many business-rules

govern the experience

• Predictions do not have a

predictable pattern

No

Import

Data

Build a

Model

Turn model

to API

Supervised Learning

Unsupervised Learning

Data Science is far too complex today

• Access to quality ML algorithms, cost is high.

• Must learn multiple tools to go end2end, from data acquisition, cleaning and prep, machine learning, and experimentation.

• Putting a model into production is time consuming.

This must get simpler, it simply won’t scale!

Azure Portal

Azure Ops Team

ML Studio

Data Scientist

HDInsight

Azure Storage

Desktop Data

Azure Portal &

ML API service

Azure Ops Team

PowerBI/DashboardsMobile AppsWeb Apps

ML API service Developer

Truth

true falseGuess

positive

𝑡𝑟𝑢𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒 𝑓𝑎𝑙𝑠𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒 𝑝𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 =𝑡𝑝

𝑡𝑝 + 𝑓𝑝

negative

𝑓𝑎𝑙𝑠𝑒 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒 𝑡𝑟𝑢𝑒 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒

𝑟𝑒𝑐𝑎𝑙𝑙 =𝑡𝑝

𝑡𝑝 + 𝑓𝑛𝑎𝑐𝑐𝑢𝑟𝑎𝑐𝑦 =

𝑡𝑝 + 𝑡𝑛

𝑡𝑝 + 𝑡𝑛 + 𝑓𝑝 + 𝑓𝑛

Reduce complexity to broaden participation

Features and Benefits

• Accessible through a web browser, no software to install;

• Collaborative work with anyone, anywhere via Azure workspace

• Visual composition with end2end support for data science workflow;

• Best in class ML algorithms;

• Extensible, support for R and Python.

Features and Benefits

• Immutable library of models, search discover and reuse;

• Rapid experimentation to create a better model

• Rapidly try a range of features, ML algorithms and modeling strategies;

• Quickly deploy model as Azure web service to our ML API service.

Train Test

Use 80% Use 20%

http://channel9.msdn.com/Events/TechEd/Europe/2014/DBI-B218

http://channel9.msdn.com/Events/TechEd/Europe/2014/CDP-B240

http://channel9.msdn.com/Events/TechEd/Europe/2014/DBI-B321

http://www.theplatform.net/2015/04/10/cloudy-machine-learning-for-the-masses/

http://www.zdnet.com/article/cloud-machine-learning-wars-heat-up/

http://www.infoworld.com/article/2911946/machine-learning/the-cloud-is-finally-making-machine-learning-practical.html