Course Outline
Introduction
- KDD vs data mining
Establishing the application domain
Establishing relevant prior knowledge
Understanding the goal of the investigation
Creating a target data set
Data cleaning and preprocessing
Data reduction and projection
Choosing the data mining task
Choosing the data mining algorithms
Interpreting the mined patterns
Summary and conclusion
Requirements
- A general understanding of databases.
Testimonials (5)
All the topics which he covered including examples. And also explained how they are helpful in our daily job.
madduri madduri - Boskalis Singapore Pte Ltd
Course - QGIS for Geographic Information System
I liked Pablo's style, the fact that he covered a lot of subjects from report design , customization with html to implementing simple ML algortithms. Good balance theoretical information / exercices. Pablo really covered all topics i was interested in and gave comprehensive answers to my questions.
Cristian Tudose - SC Automobile Dacia SA
Course - Advanced Data Analysis with TIBCO Spotfire
Actual application of spotfire and all basic functions.
Michael Capili - STMicroelectronics, Inc.
Course - Introduction to Spotfire
The thing I liked the most about the training was the organization and the location
Hamid Tuama - Ability with Innovation General Contracting (DMCC Branch)
Course - ArcGIS for Spatial Analysis
I genuinely enjoyed the lots of labs and practices.