rethinking analytics with deep learning - sas …...past to present 1950s 1980s 2010’s present...
TRANSCRIPT
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Rethinking Analytics with Deep LearningSAS User Group Malaysia
12th April, 2018
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2
Introduction to Artificial Intelligence (AI)
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Past to Present1950s 1980s 2010’s Present
Evolution
Classical
Modern
Neural Network
Machine Learning
Cognitive Intelligence
Deep Learning
Neural Network
SAS1976
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Day to Day with AI
• Imaging and Animation• Voice Assistance• Security• Personnel Assistance • Camera and video • Language Translation • Computer Gaming
• Driverless Car • Driver Assistance • Car Safety and Collation
Assistance• Journey Recommendation • IoT / Connected Car
• Smart Home Integration / Connected Home
• Home Security and Safety Prevention
• Energy Efficiency Management • Home Assistance
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From Seeing to Knowing
MODERN AI APPLICATIONS are smart, adaptive and interactive. But just how smart are we talking? The figure below provides a simple, gross model for gauging the
spectrum of machine understanding
Recognition
Simply identifying people
or things (objects, sounds, etc.).
Comprehension
Understanding how things
relate; gaining and applying
insight based on the context of a given situation.
Abstraction
Imagining or conceiving
new ideas or theories
based not just on
discrete, observed inputs
or events but on intuition
or ‘leaps of logic’ (factsnot in evidence).
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From Seeing to Knowing
Recognition
Player
Hood
Ball
Number ‘8’
Comprehension
This is a ball competition game.
Comprehension
This player is 68% more effective in mid-field.
The team has 72% chances to win this championship
This player has 62% accuracy to shoot 3 points
Identify things in a picture or video.
Relate items to each other. Evaluate and predict future state and performance.
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From Listening to Knowing
“Holy Smoke!”
Recognition Comprehension Comprehension
Translate speech verbatim. Recognize this as an exclamation,and not someone smoking during a religious experience.
Posit a positive or negative response.
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From Seeing to Knowing
Seeing
Listening
Feeling
Thinking
Responding
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AI in Practice : Healthcare
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AI in Practice : Manufacturing
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AI in Various Industry
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What Artificial Intelligence is NOT
• A crystal ball
• Autonomous robots with human intelligence
• Self-creating models
• “Out-of-the-box” everything
• Perfect model prediction
• Automated data preparation
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SAS Tactical Approach to AI
Machine Learning Natural Language Processing
Deep Learning Natural Language Understanding
Pattern Recognition ● Prediction ● Classification ● Image Recognition ● Speech to Text ●Cognitive Search ● Natural Language Interaction ● Natural Language Generation
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Powered by Viya®
MPP & GPU processingPython, Lua, Java, CASL and REST
Deep forward networks Auto encodersConvolutional networks Recurrent networks
Deep Learning
Speech to Text Natural language interactionNatural language generationBiomedical image processing
Cognitive Computing
A IM E T H O D S
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SAS Deep Learning Toolkit
SAS CAS Action Sets for Deep Learning
Develop, Training and Scoring
Hadoop Storage Engine
SAS CAS
Platform
Memory
GPU
SAS ESP
Engine
ScoringASTORE
IOT
Ap
pli
ca
tio
n
CASL, Python, R, LUA, RESTful, Mobile SDK
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What is CAS and Action Sets?
• CAS is SAS Cloud Analytic Services (CAS) pl1to execute advance analytics tasks in memory.
• CAS Action Sets is a set of SAS syntax to perform single task in SAS CAS sSer.
• Programmer can access SAS CAS server analytic capabilities.
• Why CAS?
• Supports Diversity - Range of analytics for different types of users and business problems
• Enable Scale - Data, analytics and streamlined deployment
• Empowers Trust - Unified experience, governance, stability and domain expertise
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SAS Viya Deep Learning Action Sets
Action Name Description
buildModel Create an empty deep learning model
addLayer Adds a layer to a deep learning model
dlExportModel Export a deep learning model (ASTORE)
dlImportModelWeights Import model weights from an external source
dlLabelTarget Assign the target label information
dlScore Scores a table using a deep learning model
dlTrain Trains a deep learning model
dlTune Tunes hyper-parameters for deep learning model
modelinfo Show model information
removeLayer Removes a layer from a deep learning model
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SAS Deep Learning Action Set in PythonSample Code
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SAS Deep Learning Action Set in SAS StudioSample Code
• Define CNN Layers
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