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Machine Learning Basics
Setup/Installation
Recap: Regression Models
What is Machine Learning?
Bias-Variance Tradeoff
Resampling Strategies
Exercises
Modelling
Model Selection
Regularisation
PCA, PCR & PLS
Logistic Regression
LDA & QDA
Naïve Bayes
Polynomial and Flexible Regression
Generalized Additive Models
Decision Trees
From AdaBoost to Gradient Boosting
Support Vector Machines
Exercises
Additional Materials
Exercise solutions
ML Basics Exercises
Modelling Exercises
Repository
Open issue
Index
