Scilab for Data Mining
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Process, Analyse and Visualize Data with Scilab

Scilab provides tools for data mining purposes, from the connections to the databases to the analysis tools and visualisation tools. 


 

“With Scilab, data is under my control...”
Course Synopsis

dataminimage grapData mining, or knowledge discovery, is the computer-assisted process of digging through and analysing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviours and future trends, allowing businesses to make proactive, knowledge-driven decisions.

Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing.

The phrase data mining is commonly misused to describe software that presents data in new ways. True data mining software doesn't just change the presentation, but actually discovers previously unknown relationships among the data.

Given information databases of sufficient size and quality, data mining technology can generate new business opportunities by providing these capabilities:

-Data mining automates the process of finding predictive information in large databases. Questions that traditionally required extensive hands-on analysis can now be answered quickly.

-Data mining sweeps through databases and identify previously hidden patterns in one step.

 

Course Objectivesdataminimage excelc

This course is intended as a practical hands-on experience to data mining with Scilab for the use in engineering and sciences. As an open source software, Scilab provides a powerful computing environment for your analysis. A series of hands-on exercises will help you to understand better and more efficiently in the topics outlined here

Who Must Attend

Engineers, researchers, scientists from academic, science and engineering or simply anyone who wants to work and retrieve valuable information from the available data.

Prerequisites

Basic knowledge of computer operation and data analysis are preferred. We will bring you to speed in understanding in using the Scilab program


Course Outline
Understanding Scilab
  • Overview of Scilab
This session will provide basic understanding of Scilab
and how it could be used for data mining.
 
 
Importing and Exporting Data
  • Importing data from Scilab Workspace
  • Importing data from files (txt, xls, csv, etc)
  • Importing data from web interface
  • Importing data from database
Learn how to import and exporting data from and to
various sources, such as into files in different formats,
database, or even to the cloud.
 
 
Processing Data
  • Dealing with Outliers
  • Dealing with NaNs and Infs
  • Removing duplicates data
  • Filtering data
Processing data is an important stage before jumping 
into data visualization or modelling. Irrelevant data
could cause wrong model which yield to the wrong interpretation of the data.
 
Visualizing Data
  • Line Plot
  • Bar Chart and Pie Chart
  • Histograms
  • Matrix Plot
  • 3D Visualisation
Different methods of Visualizing data help us to have better understanding of data. This will give us a big picture of what we are going to do with the data before jumping into it in "blind" and end up with "rubbish in, rubbish out".
 
 
Conventional Analysis
  • Statistical Analysis
  • Correlation and Linear Regression
  • Data Fitting

Understanding basic concept of statistical analysis of data, study the meaningful relations of the data and representing data with equation.

 

Artificial Intelligence
  • Classification and Clustering techniques
  • Fuzzy Logic Example (FLS)
  • Neural Network Example (NN)
  • Support Vector Machine Example (SVM)
Exploring more advance methods in analysing the data, including the artificial intelligence methods which as Fuzzy, Neural and SVM.

To obtain details of the course (fee, location and etc.), kindly obtain a registration form by email tina@tritytech.com

Provide us with your name, organization & mobile contact number.

You may also call us at +603-80637737 or fill up our Training Enquiry form.

 

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