Teaching > Machine Learning in R > Problem Sets
Problem Sets
Problem Set 1: Linear Methods
Task 1: Multiple Linear Regression
Task 2: Classification (Logit/LDA/k-NN)
Task 3: Bootstrapping
Task 4: Linear Model Selection and Regularization
Problem Set 2: Non-Linear Methods
Task 1: Non-Linear Regression Techniques
Task 2: Tree-Based Methods
Task 3: Support Vector Machines
Problem Set 3: Deep Learning & Unsupervised Learning
Task 1: Feed-Forward Neural Networks I
Task 2: Feed-Forward Neural Networks II
Optional: Pretrained Neural Networks
Task 3: Unsupervised Learning (Clustering)