This course on Data Mining with Weka aims to teach learners the fundamentals of data mining using the Weka software. By the end of the course, students will be able to explore datasets, build classifiers, use filters, visualize data, conduct training and testing, understand cross-validation, decision trees, regression techniques, support vector machines, and ensemble learning. The course employs a hands-on approach, allowing students to practice with real datasets and apply various data mining techniques. This course is suitable for individuals interested in learning data mining concepts and applying them using the Weka software.
Overview
Syllabus
Data Mining with Weka: Trailer.
Data Mining with Weka (1.1: Introduction).
Data Mining with Weka (1.2: Exploring the Explorer).
Data Mining with Weka (1.3: Exploring datasets).
Data Mining with Weka (1.4: Building a classifier).
Data Mining with Weka (1.5: Using a filter ).
Data Mining with Weka (1.6: Visualizing your data).
Data Mining with Weka (2.1: Be a classifier!).
Data Mining with Weka (2.2: Training and testing).
Data Mining with Weka (2.3: Repeated training and testing).
Data Mining with Weka (2.4: Baseline accuracy).
Data Mining with Weka (2.5: Cross-validation).
Data Mining with Weka (2.6: Cross-validation results).
Data Mining with Weka (3.1: Simplicity first!).
Data Mining with Weka (3.2: Overfitting).
Data Mining with Weka (3.3: Using probabilities).
Data Mining with Weka (3.4: Decision trees).
Data Mining with Weka (3.5: Pruning decision trees).
Data Mining with Weka (3.6: Nearest neighbor).
Data Mining with Weka (4.1: Classification boundaries).
Data Mining with Weka (4.2: Linear regression).
Data Mining with Weka (4.3: Classification by regression).
Data Mining with Weka (4.4: Logistic regression).
Data Mining with Weka (4.5: Support vector machines).
Data Mining with Weka (4.6: Ensemble learning).
Data Mining with Weka (5.1: The data mining process).
Data Mining with Weka (5.2: Pitfalls and pratfalls).
Data Mining with Weka (5.3: Data mining and ethics).
Data Mining with Weka (5.4: Summary).
Taught by
WEKA MOOC
