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Course Links

Links in italic are either course or TA recommended.

Pre Req Learning

• The Analytics Edge - MOOC from MIT, available on edX also
• -Introduction to Statistical Learning (ISLR)-
• DataCamp: Introduction to R
• DataCamp: Introduction to Machine Learning with R
• A short introduction to the caret package

Weeks

Resources tied to specific weekly homeworks/lessons

Week 1

• SVM Explained
• KNN Simple Example
• StackExchange: What is the influence of C in SVMS with the linear kernel?
• Support vector machines, kernels, and applications in computational biology - Slides by Jean-Philippe Vert, go more in-depth than the lecture videos on SVM and provide stand-in slides
  • Youtube: Support Vector Machines Clearly Explained-
  • Youtube: Support Vector Machine - Fun and Easy Machine Learning-
  • Medium: Support Vector Machine with Math-

Week 2

• K Means Clustering in R Example
• DataCamp: K-Means Clustering in R Tutorial
• DataCamp: Machine Learning Toolbox: Chapter 1 - Good walkthrough of cross validation tactics
• StackExchange: How does cross-validation in train (caret) precisely work?
• Medium: K Fold Cross Validation and Other Techniques - Good visuals
• StackExchange: Interpreting the results of kmeans

Week 3

Week 4

• UC Business Analytics R Programming Guide - Exponential Smoothing
• otexts: 7.3 Holt-Winters’ seasonal method
• DataCamp: Forecasting Using R

Week 5

• DataCamp: Linear Regression R

Week 6

• DataCamp: PCA Analysis in R

Week 7

• Plotting with rpart.plot
• StackExchange: Rpart Complexity Parameter
• StackExchange: Understanding of minbucket in rpart
• Towards Data Science: Random Forest in R
• UC Business Analytics: Random Forests - R based guide

Week 8

• DataCamp: Regularization: Ridge, Lasso and Elastic Net
• R-Bloggers: Ridge Regression & Lasso
• StackExchange: How to interpret glmnet plot?
• Stanford: GLM Introduction

Week 9

• Fractional Factorial Design