1© 2015 The MathWorks, Inc.

Data Analytics with MATLAB

Adam Filion

Application Engineer

MathWorks, Inc.

2

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

3

Challenges with Data Analytics

Aggregating data from multiple sources

Cleaning data

Choosing a model

Moving to production

4

Challenges with Data Analytics

Aggregating data from multiple sources

Cleaning data

Choosing a model

Moving to production

5

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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6

Challenges with Data Analytics

Aggregating data from multiple sources

Cleaning data

Choosing a model

Moving to production

7

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

8

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

9

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

10

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

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.