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1© 2015 The MathWorks, Inc.
Data Analytics with MATLAB
Adam Filion
Application Engineer
MathWorks, Inc.
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Goal:
Implement a tool for easy and accurate computation of day-ahead system
load forecast
Requirements:
Acquire and clean data from multiple
sources
Accurate predictive model
Easily deploy to production environment
Case Study: Day-Ahead Load Forecasting
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Challenges with Data Analytics
Aggregating data from multiple sources
Cleaning data
Choosing a model
Moving to production
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Challenges with Data Analytics
Aggregating data from multiple sources
Cleaning data
Choosing a model
Moving to production
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Machine LearningCharacteristics and Examples
Characteristics
– Too many variables
– System too complex to know
the governing equation(e.g., black-box modeling)
Examples
– Pattern recognition (speech, images)
– Financial algorithms (credit scoring, algo trading)
– Energy forecasting (load, price)
– Biology (tumor detection, drug discovery)
93.68%
2.44%
0.14%
0.03%
0.03%
0.00%
0.00%
0.00%
5.55%
92.60%
4.18%
0.23%
0.12%
0.00%
0.00%
0.00%
0.59%
4.03%
91.02%
7.49%
0.73%
0.11%
0.00%
0.00%
0.18%
0.73%
3.90%
87.86%
8.27%
0.82%
0.37%
0.00%
0.00%
0.15%
0.60%
3.78%
86.74%
9.64%
1.84%
0.00%
0.00%
0.00%
0.08%
0.39%
3.28%
85.37%
6.24%
0.00%
0.00%
0.00%
0.00%
0.06%
0.18%
2.41%
81.88%
0.00%
0.00%
0.06%
0.08%
0.16%
0.64%
1.64%
9.67%
100.00%
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Challenges with Data Analytics
Aggregating data from multiple sources
Cleaning data
Choosing a model
Moving to production
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MATLAB
MATLAB
Compiler SDK
C/C++ExcelAdd-in JavaHadoop
.NET
MATLAB
Compiler
MATLABProduction
Server
StandaloneApplication
Which Product will Fit Your Needs?
MATLAB Compiler for 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
Python
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MATLAB
Desktop
Deployed AnalyticsMATLAB Production Server
MATLAB
Production
Server
Web
Application
Server
MATLAB
Production Server
Requ
est B
roke
r
CTF
Apache Tomcat
Web Server/
Webservice
Weather
Data
Energy
Data
Predictive
Models
Train in
MATLAB
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Data Analytics Products
Develop
Predictive ModelsAccess and
Explore DataPreprocess Data
Integrate Analytics
with Systems
MATLAB
MATLAB Production Server
Statistics and Machine Learning ToolboxDatabase Toolbox
Neural Network ToolboxData Acquisition Toolbox
Image Processing Toolbox
Signal Processing Toolbox Computer Vision System Toolbox
Curve Fitting Toolbox
MATLAB Compiler
MATLAB Compiler SDK
Parallel Computing Toolbox, MATLAB Distributed Computing Server
Mapping Toolbox
Image Acquisition Toolbox
OPC Toolbox
Econometrics ToolboxUsed in today’s demo
Additional Data Analytics
products
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Key Takeaways
Data preparation can be a big job; leverage
built-in MATLAB tools and spend more time
on the analysis
Rapidly iterate through different predictive
models, and find the one that’s best for your
application
Leverage parallel computing to scale-up your analysis to large datasets
Eliminate the need to recode by deploying your MATLAB algorithms into
production
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11© 2015 The MathWorks, Inc.
© 2015 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks
for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.