Introducing Precictive Analytics
• Foundations
– Terms and Definitions
– Objectives
– Methodology
• „Prediction as a service“
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8.3.2016
Oxford AI (Microsoft)
Google ML Service
Amazon ML Service
IBM Watson Service
Wit.ai
etc.
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Business Intelligence
Business intelligence (BI) is an umbrella term that
includes the applications, infrastructure and tools,
and best practices that enable access to and
analysis of information to improve and optimize
decisions and performance.
Source: Gartner IT Glossary, Own highlighting
http://www.gartner.com/it-glossary/business-intelligence-bi/
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Analytics
• Analytics has emerged as a catch-all term for
a variety of different business intelligence (BI)and application-related initiatives. […]
Increasingly, “analytics” is used to describe
statistical and mathematical data analysis
that clusters, segments, scores and predicts
what scenarios are most likely to happen […
based on … ] huge mounds of internally
generated and externally available data.
Source: Gartner IT Glossary, Own highlighting and abbreviation
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Big Data
• Big data is high-volume, high-velocity and/or
high-variety information assets that demand
cost-effective, innovative forms of information
processing that enable enhanced insight,
decision making, and process automation.
Source: Gartner IT Glossary, Own highlighting
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Machine Learning
Machine learning is a method of data analysis
that automates analytical model building. Using
algorithms that iteratively learn from data,
machine learning allows computers to find
hidden insights without being explicitly
programmed where to look.
(Source: SAS, http://www.sas.com/en_us/insights/analytics/machine-learning.html)
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Data Science (I)
• The field of data science is emerging at the
intersection of the fields of social science and
statistics, information and computer science,
and design.
(Source: University of Berkeley
https://datascience.berkeley.edu/about/what-is-data-science/)
• Data Science is an essential skill for analyzing
and deriving useful insights from data, big and
small.
(Source: https://www.edx.org/course/data-science-machine-learningessentials-microsoft-dat203x-0#!)
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Data Science (II)
• Data Science is an interdisciplinary field about
processes and systems to extract knowledge
or insights from data in various forms, either
structured or unstructured, which is a
continuation of some of the data analysis
fields such as statistics, data mining, and
predictive analytics, similar to Knowledge
Discovery in Databases.
(Source: Wikipedia, Retrieved at 3.4.2016)
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Relating Definitions
Business
Analytics
Intelligence
Machine Learning
Analytics  Data Science
Business Intelligence  Data Science
Machine Learning  Analytics
Business Intelligence  Analytics  
Data Science
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Agenda
• Foundations
– Terms and Definitions
– Objectives
– Methodology
• „Prediction as a service“
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8.3.2016
Oxford AI (Microsoft)
Google ML Service
Amazon ML Service
IBM Watson Service
Wit.ai
Usw.
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Objectives of “Predictive Analytics”
Unknown
Data
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𝑓
Prediction
Find a function f
Such that Predicition is as True as possible…
… for arbitrary unknown data
We call f a prediction model
Prediction is either a number (regression) or a
category (classification)
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Approach “Supervised learning”
Unknown
Data
𝑓
Known
Outcome
• Learn prediction model f using known data, such that
• f produces known output…
• … without loosing generality of f wrt. Unknown data
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How to ensure generality of f
Known data
With
Known output
Test Data
(validate f)
Training Data
(learn f)
• Split known data into two parts
– Use larger part (typically 70%) for learning f
(aka. Training Data Set)
– Use smaller part (1 – train) for testing how f works
for “unknown” data (aka. Test Data Set)
– Accept prediction model f ,
if Prediction matches “Known Outcome”
well enough
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Actual Outcome vs. Prediction
• Aka. Confusion Matrix
• Compare prediction generated by f with
actual known data (available for test data)
Actual
Known
Outcome
Prediction
Yes
No
Yes
Correct
Wrong
No
Wrong
Correct
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Agenda
• Foundations
– Terms and Definitions
– Objectives
– Methodology
• „Prediction as a service“
–
–
–
–
–
–
8.3.2016
Oxford AI (Microsoft)
Google ML Service
Amazon ML Service
IBM Watson Service
Wit.ai
Usw.
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“Prediction as a service”
• Company created the prediction model f using their
data
• You just use the f and obtain a prediction using your
data, (commercial) services available for
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OCR
Voice Recognition
Language Translation
Computer Vision
Speech Synthesis
…
• Can use services from Google, Microsoft, IBM, Amazon,
and others…
• Mostly $$$ (Pay as you go) with free trial
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Agenda
• Foundations
– Terms and Definitions
– Objectives
– Methodology
• „Prediction as a service“
–
–
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–
–
8.3.2016
Oxford AI (Microsoft)
Google ML Service
Amazon ML Service
IBM Watson Service
Wit.ai
Usw.
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Microsoft Cognitive Services
(fka Project Oxford)
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Microsoft Cognitive Services Overview
Source: https://www.microsoft.com/cognitive-services (Retrieved April 2016)
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Object Recognition
Source: https://www.microsoft.com/cognitive-services/en-us/computer-vision-api
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Celebrity Recognition
Source: https://www.microsoft.com/cognitive-services/en-us/computer-vision-api
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OCR (Text Recognition)
Source: https://www.microsoft.com/cognitive-services/en-us/computer-vision-api
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Hands On
• Try Yourself
https://www.microsoft.com/cognitive-services/enus/computer-vision-api
• Developer View (Requires Free Registration)
https://dev.projectoxford.ai/docs/services/56f91f2d778d
af23d8ec6739/operations/
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Agenda
• Foundations
– Terms and Definitions
– Objectives
– Methodology
• „Prediction as a service“
–
–
–
–
–
–
8.3.2016
Oxford AI (Microsoft)
Google ML Service
Amazon ML Service
IBM Watson Service
Wit.ai
Usw.
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Google Cloud Vision API
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Detects objects on image
Detects inappropriate content (FamilyFilter)
Detect sentiment (happyiness, age, gender)
Extract Text (OCR – Object Recognition)
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Google Cloud Vision API Capabilities
Source: https://cloud.google.com/vision/
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Google Cloud Vision API Pricing
Source: https://cloud.google.com/vision/docs/pricing (Retrieved April 2016)
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Demo – Image Labeling
Your image
Source: https://cloud.google.com/vision/docs/getting-started
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Demo – Image Labeling
Request
Available Types
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Demo – Image Labeling
97,9% Dog
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Demo 2 – Violence Detection
Source: Spartacus TV Series
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Demo 2 – Violence Detection
Object Recognition
Safe Search Recognition
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Summary / Learning Questions
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What is a prediction model ?
What is required to use a prediction model?
How is a prediction model generated ?
How to assess the quality of a prediction?
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