modelle für die zukunft dank prädiktiver datenanalyse...develop embedded systems with analytics...
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11© 2015 The MathWorks, Inc.
Modelle für die Zukunft dank
prädiktiver Datenanalyse
Jérémy Huard, MathWorks
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𝜕𝑢
𝜕𝑡− 𝛼
𝜕2𝑢
𝜕𝑥2+𝜕2𝑢
𝜕𝑦2+𝜕2𝑢
𝜕𝑧2= 0
Thermodynamic properties
Temperatures change Humans have comfort bounds
Electricity demand varies
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Traits of Data Analytics applications
1. Diverse and/or Big Data
2. Advanced Algorithms
3. Deployment
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Why MATLAB?
Develop embedded
systems with analytics
powered functionality
3
Enable Domain
Experts to be
Data Scientists
2
Analytics that increasingly
require both business
and engineering data
1
Data Scientist
Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4
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77
Why MATLAB?
Develop embedded
systems with analytics
powered functionality
3
Enable Domain
Experts to be
Data Scientists
2
Data Scientist
Smarter Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4
Analytics that increasingly
require both business
and engineering data
1
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Business and Engineering Data
“No matter what industry our client is in, and no matter what data they ask us to analyze—text, audio,
images, or video—MATLAB enables us to provide clear results faster.”
Dr. G Subrahmanya VRK Rao, Cognizant
File I/O
• Text
• Spreadsheet
• XML
• CDF/HDF
• Image
• Audio
• Video
• Geospatial
Repositories
• Databases
• Hadoop
File I/O
• Text
• Spreadsheet
• XML
Business and Transactional Data Engineering, Scientific, and Field Data
Web Sources
• HTML
• Mapping
• Financial datafeeds
• RESTful
• JSON
Communication Protocols
• CAN (Controller Area Network)
• DDS (Data Distribution Service)
• OPC (OLE for Process Control)
• XCP (eXplicit Control Protocol)
Real-Time Sources
• Sensors
• GPS
• Instrumentation
• Cameras
• Communication systems
• Machines (embedded systems)
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Data handling and visualization
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Feature Engineering – Extracting Information from DataData type Common Techniques for Deriving Features
Sensor data Peak analysis
Pulse and transition metrics
Spectral measurements (power, bandwidth, mean frequency, median frequency)
Image and video data Bag of visual words
HOG (Histogram of Oriented Gradients)
Minimum Eigenvalue algorithm
Local feature descriptors
Edge detection
Transactional data Decomposing timestamps into components (day, month, day of
week, etc.)
Calculation of aggregate values
Complexity reduction
High-quality domain-specific libraries
Signal Processing
Image Processing
Computer Vision
Statistics
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1111
Why MATLAB?
Develop embedded
systems with analytics
powered functionality
3
Analytics that increasingly
require both business
and engineering data
1
Data Scientist
Smarter Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4
Enable Domain
Experts to be
Data Scientists
2
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Enabling Domain Experts to be Data Scientists
Symbolic
Computing
Neural
Networks
OptimizationSignal
Processing
Image
Processing
Control
Systems Financial
Modeling
Apps Language
Machine
LearningStatistics
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Built-in algorithms
Clustering
Regression
Classification
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Interactive Apps
to focus on machine learning,
not programing
Neural network Apps
Classification Learner App
Features
Train models
Assess results
Export models to the MATLAB
or generate MATLAB code
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1515
Why MATLAB?
Enable Domain
Experts to be
Data Scientists
2
Analytics that increasingly
require both business
and engineering data
1
Data Scientist
Smarter Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4Develop embedded
systems with analytics
powered functionality
3
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Smarter Embedded Systems
INTEGRATION
IMPLEMENTATION
DESIGN
TE
ST
AN
D V
ER
IFIC
AT
ION
RESEARCH REQUIREMENTS
MCU DSP FPGA ASIC
VHDL,
VerilogC, C++
Environment Models
Physical Components
Algorithms
Structured
Text
PLC
GM
Climate control
Airbus
Battery management
Daimler
Cruise controller
manroland
Printing presses
Sonova
Hearing implantsWeinmann
Transport ventilator
Festo
Industrial robots
FLIR
Thermal imaging
ABB
Smart Grid controller
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1717
Why MATLAB?
Develop embedded
systems with analytics
powered functionality
3
Enable Domain
Experts to be
Data Scientists
2
Analytics that increasingly
require both business
and engineering data
1
Data Scientist
Smarter Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4
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MATLAB
ExcelAdd-in
Hadoop
MATLAB
Compiler
StandaloneApplication
Deploying Algorithms to Enterprise Systems
MATLAB Compiler enables sharing MATLAB programs without integration programming
MATLAB Compiler SDK provides implementation and platform flexibility for software developers
MATLAB Production Server provides the most efficient development path for secure and
scalable web and enterprise applications
MATLAB
Compiler SDK
C/C++
Java
.NET
MATLABProduction
Server
Python
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Enterprise Integration – Forecasting Model
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2020
MATLAB Differentiators
Develop embedded
systems with analytics
powered functionality
3
Enable Domain
Experts to be
Data Scientists
2
Analytics that increasingly
require both business
and engineering data
1
Data Scientist
Smarter Embedded Systems
DATA
• Engineering, Scientific, and Field
• Business and Transactional
Business Systems
Develop analytics to run on both enterprise and
embedded platforms
4
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Learn More
Machine Learning
mathworks.com/machine-learning
Training
Presentations
Consulting