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Deep Learning Finding Deep Structures in Data Chris Orwa 3 rd March 2016

Deep learning

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Page 1: Deep learning

Deep LearningFinding Deep Structures in Data

Chris Orwa3rd March 2016

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What is Deep Learning?

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“A branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data” - Wikipedia

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Tenets of Deep Learning• Multiple Processing Layers• Model data in high abstraction• Learn from abstraction

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Our Processing Layers

•Principal Component Analysis• Mantel’s Test• Time Series• Group Theory

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Principal Component Analysis • Allow data representation in alternative co-ordinate system. • Provides for dimensionality reduction• Easy to visualize• Emphasize variation in data

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Run PCA on Questionnaire

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Inconsistency!

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Track Changes

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Inconsistency!

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How can I better capture the changes?

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Mantel’s Permutation Test

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Mantel’s Test

• Conceived by Nathan Mantel in 1967 • Used to track cancer epidemics• Test correlation between two matrices• Supported in R by APE package

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Modify Code

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Modify Code Cont’d

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What Did I Get?

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Same Test on Twitter Data #EastleighBlast

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Matrix Representation

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Same Test on Forex Data CADUSD,EURGBP, USDJPY

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Observations!

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There are Two Types of Data• Stable Structure: Does not vary with variation.• Unstable Structure: Varies with variation.

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Application!

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Scenario I: Stable Structures

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Lend Themselves to Two Important Fields

• Spatial Principal Component Analysis

• Group Theory

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Library(adegenet)

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Scenario II: Unstable Structures

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Two Application Areas

•Seasonal Market-Basket Analysis

• Tracking Online Conversations

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Sentiment Analysis

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Thank You!blackorwa.com

@blackorwa


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