Exam Case study and exercises in R for second half of the Introduction to Machine Learning course.
We explore analytical cases with multiple R visualizations to validate our hypotheses. We also check for possible logical fallacies and confounding variables in suggested case solutions. Additionally, unsupervised learning models such as PCA, clustering approaches, association rule mining, network analysis etc. are studied in detail.