Coursework from EC3389 - Big Data (Statistical Learning Theory and Applications) Topics covered include:
- Linear models
- Shrinkage (Ridge, LASSO)
- Resampling Methods
- Classification (Logit, K-Means, KNN)
- Non-linear modeling (Splines, Polynomial Regression)
- Tree-based methods (Decision Trees, Bagging, Random Forests)
- Support Vector Machines
- Unsupervised Learning (PCA, K-Means)
Folder contains programming portion of course assignments
Contains ipython notebooks from applied portion of the course
##Final Project Final project was a classification task, predicting whether URLs are malicious or benign. Final_Writeup.pdf is LaTeX compiled pdf of final submission, Malicious_URLs.ipynb is the code for the project.