Welcome to psy300!

This book contains the materials for the Statistical Methods Seminar of the Data Science and Machine Learning Master’s Programme at Carl von Ossietzky Universität Oldenburg. We will explore and discuss the contents of the lecture in a practical way using Python.

Table of contents

Machine Learning Basics

• Setup/Installation
• Recap: Regression Models
• What is Machine Learning?
• Bias-Variance Tradeoff
• Resampling Strategies
• Exercises

Modelling

• Model Selection
• Regularisation, PCR & PLS
• Generalized Additive Models
• K-Nearest Neighbors
• LDA & QDA
• Naïve Bayes
• Decision Trees
• Support Vector Machines
• Principal Component Analysis
• Exercises

Additional Materials

• Exercise solutions

Additional resources

• https://www.statlearning.com/

• https://mlu-explain.github.io/

• https://animlbook.com/

• https://geostatsguy.github.io/MachineLearningDemos_Book