Data Mining and Machine Learning Shaina Race, PhD

Data Mining

Topic	Video	Slides + Notes	Code + Data	Exercises + Homework
Introduction to Data Mining (Modeling Part I) (Self-paced by 10/5)	Bias-Variance Tradeoff (Train-Valid-Test) Missing Values Transactional Data Variable Transformations	Introduction		Exercises (Solutions)
Association Analysis		Association	Grocery Data (SAS) Viya Code Association Analysis in R Association Analysis in Python Grocery Data (.csv)	Exercises (Solutions) Due BY 9/25 5pm: Homework Homework Data (.csv) public.orderData2 (SAS Viya) Submit link Due BY 9/25 11:59pm: Homework Quiz
Classification and Regression Trees (CART) Part 1		CART	Viya Demo 1 Telco Churn(.csv) Viya Tree Details A Python run-through	Exercises (#2,3,5,7,8) (Solutions)
Classification and Regression Trees (CART) Part 2		CART	Viya Demo 2 Breast Cancer (SAS Dataset) Demo 2 in R Breast Cancer Descript'n (.txt) Decision Trees in R Breast Cancer (Rdata)	Exercises (ALL problems) (Solutions) Homework Homework Data (.csv) Homework Data (.RData) Homework Data Dict. (.txt) Submit link Due BY Friday 10/16 11:59pm: Homework Quiz
Clustering Part 1 k-means		Clustering	Clustering in R (Code) Adult Data (.RData) Adult Data (.csv)
The Curse of Dimensionality (self-paced by 10/9)	Curse of Dimensionality.mp4	Slides		Carl Sagan's Introduction to Flatland (Just for fun)
Clustering Part 2 Hierarchical Clustering		Clustering	HierarchicalClust using k-means centroids in R (Adult data) Clustering in SAS (code) Breast Cancer (SAS Dataset)	Exercises (Solutions) (Detail Solution Problem 2)
Clustering Lab		Choose your Own Adventure - Clustering	TeenSNS Data (.sas7bdat) (also in public library) TeenSNS Data (.csv) TeenSNS Data (.RData) TeenSNS Description (.txt)	Link to Submit Profiles One submission per team!
k-NearestNeighbor		kNN	PenDigitTrain (SAS) PenDigitTest (SAS) PenDigit Description (.txt) kNN in Base SAS (.pdf) kNN in R PenDigits.Rdata	kNN Exercises (kNN Solutions)
Modeling Part II (self-paced by 10/19)		Model Evaluation		Exercises (Solutions)
Ensemble Models		Ensemble Models	Telco Churn(.csv)
Review		Review Slides (with solutions)
Exam Open Monday 10/19 Due Friday 10/23 11:59pm You may use any notes but may not accept exam-specific help from another person
Ensemble Clustering (Faculty Workshop - 10/1)	Recording	Consensus Clustering	R Code Adult Data (.RData) Adult Data (.csv)

Machine Learning

Topic	Video	Slides + Notes	Code + Data	Exercises + Homework
MODELING COMPETITION .RData (Train, Valid, Test) .csv Training Data .csv Validation Data .csv Test Data (for submission) Project Description Sample Submission
Bagging and Random Forests		Random Forests Reference Text	Random Forests in R (.pdf) Random Forests in R (Code) PenDigits.Rdata PenDigitTrain (SAS) PenDigitTest (SAS) PenDigit Description (.txt) Python Tutorial	Exercises (#1a-f, 2, 3) (Solutions)
Boosting Gradient Boosting		Gradient Boosting Reference Text	Gradient Boosting in R Python Tutorial	Exercises (Solutions)
Regularized Regression Ridge and LASSO	Regularized Regression	Ridge/Lasso in R (.pdf) Ridge/Lasso in R (Code) Hitters Data (Rdata) Hitters Description Hitters Data (SAS) Python Tutorial	Exercises (Solutions)
Neural Networks		Neural Networks Backpropogation Example (Requires Calculus) Backpropogation Video (3blue 1brown)	Neural Networks in R Concrete Data (SAS) Concrete Data (.RData) Concrete Description (.txt)	Exercises (Solutions)
MIDTERM QUIZ (ML Topics 1-4 PLUS k-means clustering)
Support Vector Machines (SVM) and Kernels		Support Vector Machines	SVM + Grid Search (R Code) SVM + Grid Search in R (.pdf) Customer Churn (Rdata) Customer Churn Train (SAS) Customer Churn Train (SAS) Support Vector Regression in R	Exercises (Solutions)
Naive Bayes Classifier		Naive Bayes	Naive Bayes in R (.pdf) SMS Data (.RData) Naive Bayes in R (.R) PCA Intro to SMS Data (.R)
Model Agnostic Interpretability Individual Conditional Expectation (ICE) Partial Dependence (PDP) Permutation Variable Importance		Model Interpretability Online Textbook	Code to create plots from Slides
Model Agnostic Interpretability Accumulated Local Effects (ALE) LIME Shapley Values		Model Interpretability Online Textbook	Code to create plots from Slides
FINAL QUIZ (ML Topics 5-8 PLUS Regularized Regression) DUE: FRIDAY 11/20 11:59PM
Explainable Boosting Machine (Faculty Workshop - 4/1)	Recording	Slides	notebook

Cool Links

Cheat Sheets for Open Source Data Science.

Finding the k in k-means with Python

NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set

Visualizing and Comparing Decision Boundaries of Classifiers. Another example with code in iPython notebook format is here.

The Neural Network Playground.

Tutorial on Sequence Analysis in R, including exploration using other variables (sequences by gender, for example)
Part 1 (Sequence Analysis and Plots).
Part 2 (Clustering).
Part 3 (Advanced Analysis).

DataCamp Tutorials/Courses

Complete (teachy) Regularized Regression Tutorial Python

The Illustrated Cliff Notes for Introduction to Statistical Learning Textbook.

Gradient Boosting with Scikit-Learn, XGBoost, LightGBM, and CatBoost.