Lecture Videos

This page contains lectures videos for the data mining course offered at RPI in Fall 2019.

Aug 30, Introduction, Data Matrix

Sep 6, Data Matrix: Vector View

Sep 10, Numeric Attributes: Statistical and Algebraic View

Sep 13, Covariance Matrix, Eigenvalues, Principal Component Analysis (PCA)

Sep 17, PCA, Normal Distribution

Sep 20, High Dimensional Data

Sep 24, Kernel Methods

Sep 27, Kernel Method and Kernel PCA

Oct 4, Linear Regression (Algebraic and Geometric Views)

Oct 8, Linear Regression: QR Factorization, Ridge Regression

Oct 11, Linear Regression: Kernel Regression, Logistic Regression

Oct 15, Logistic Regression

Oct 18, Neural Networks

Oct 22, Neural Networks: Multilayer Perceptrons

Oct 25, Neural Networks: Deep Networks, Recurrent Networks

Oct 29, Recurrent Neural Networks (RNNs)

Nov 5, LSTMs and Convolutional Neural Networks (CNNs)

Nov 8, Support Vector Machines (SVMs)

Nov 12, SVMs and Naive Bayes

Nov 15, Clustering: Kmeans

Nov 19, Clusering: Expectation Maximization, Spectral Clustering

Nov 22, Spectral and Graph Clustering, Frequent Pattern Mining

Nov 26, Frequent Pattern Mining (Itemsets)

Dec 3, Itemset Mining, Model Evaluation: Bias and Variance

Dec 6, Model Evaluation: Cross Validation, Emsemble Models