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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)
Practical classes, exercises, possibility of applying the discussed solutions in practice.
Agnieszka - Izba Administracji Skarbowej
Course - Platforma analityczna KNIME - szkolenie kompleksowe
Machine Translated
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
positive atmosphere during training
Piotr Wojciechowski - Centrum Informatyki Resortu Finansow
Course - Data Mining with Python
Machine Translated
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.
