CMSC 422 (Section 0101): Introduction to Machine Learning
Welcome to the CMSC 422 course webpage for Spring 2019.
CMSC 422 (Section 0101) is currently being taught by Soheil Feizi.
See UMD Web Accessibility.
Announcements
Lecture 1 (1/29): Welcome to Machine Learning
Lecture 2 (2/5): Review of Probability and Linear Algebra
Lecture 3 (2/7): Decision Trees
Lecture 4 (2/12): Nearest Neighbor Classification
Lecture 5 (2/14): KMeans
Lecture 6 (2/19): Perceptron
Lecture 7 (2/21): Perceptron Convergence Analysis
Lecture 8 (2/26): Linear Classifiers, Gradient Descent and Hinge Loss
Lecture 9 (2/28): Gradient Descent, Analysis
Lecture 10 (3/5): Probabilistic View of ML + Naive Bayes
Lecture 11 (3/7): Midterm
Lecture 12 (3/12): Logistic Regression
Lecture 13 (3/14): Logistic Regression+ Cross Entropy Loss
Lecture 14 (3/26): Logistic Regression+ Multilabel Classification
Lecture 15 (3/28): Neural Networks
Lecture 16 (4/2): Nonlinear Regression + Back Propagation
Lecture 17 (4/4): Multi Label Classification + Momentum method
Lecture 18 (4/9): PCA
Lecture 19 (4/11): PCA II
Lecture 20 (4/16): PCA + AutoEncoders
Lecture 21 (4/18): AutoEncoders
Lecture 22 (4/23): Kernels
Lecture 23 (4/25): Kernels + Support Vector Machines
Lecture 24 (4/29): Support Vector Machines
Lecture 25 (5/2): Support Vector Machines II
