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Course Outline
Introduction
- Overview of Weka
- Understanding the data mining process
Getting Started
- Installing and configuring Weka
- Understanding the Weka UI
- Setting up the environment and project
- Exploring the Weka workbench
- Loading and Exploring the dataset
Implementing Regression Models
- Understanding the different regression models
- Processing and saving processed data
- Evaluating a model using cross-validation
- Serializing and visualizing a decision tree model
Implementing Classification Models
- Understanding feature selection and data processing
- Building and evaluating classification models
- Building and visualizing a decision tree model
- Encoding text data in numeric form
- Performing classification on text data
Implementing Clustering Models
- Understanding K-means clustering
- Normalizing and visualizing data
- Performing K-means clustering
- Performing hierarchical clustering
- Performing EM clustering
Deploying a Weka Model
Troubleshooting
Summary and Next Steps
Requirements
- Basic knowledge of data mining process and techniques
Audience
- Data Analysts
- Data Scientists
14 Hours
Testimonials (5)
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
Course - Data Vault: Building a Scalable Data Warehouse
Very useful in because it helps me understand what we can do with the data in our context. It will also help me
Nicolas NEMORIN - Adecco Groupe France
Course - KNIME Analytics Platform for BI
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course - Foundation R
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
Course - From Data to Decision with Big Data and Predictive Analytics
The example and training material were sufficient and made it easy to understand what you are doing.
