Description
- Introduction and business scenario
- Loading data and summary statistics
- Visualising data
- Advanced data preparation, joins
- Feature generation and feature engineering
- Support Vector Machines
- Neural Networks
- Logistic Regression
- Advanced performance criteria
- ROC Plots
- Comparison between Models
- Feature Selection: Forward Selection, Backward Elimination
- Principal Components Analysis
- Performance (Cost) Model Optimization
- Outlier Detection
