Get the CS 3244 calendar as an link for use in calendaring applications, or see the calendar as a web page (never miss a class again, yeah right). Links to lecture notes and tutorials will start to function around the time the respective subject is covered in class.
New We note that Machine Learning is a subject with a lot of very good expertise and tutorials out there. It is best to tap on these resources, as they have good production quality and are more condensed, possibly saving you time. However, we still think in-class lecture is helpful to build better connection with the materials for certain topics.
As such, portions of this class will be flipped; i.e., you will be asked to watch such videos explaining the concepts on your own first, and then come to class for a class-wide recitation, in which Min will guide you through some exercises. Flipped lessons are marked with flipped, but these are preliminary and are likely to change.
|Week 1 (15 Aug)||Administrivia and Supervised Learning|
|Week 2 (22 Aug)||flipped Reviews: Probability, Statistics, and Linear Algebra|
|Week 3 (29 Aug)||Feasibility of Learning and Linear Regression|
|Week 4 (5 Sep)||flipped Logistic Regression and Gradient Descent|
|Week 5 (12 Sep)||Support Vector Machines and Kernelization|
|Week 6 (19 Sep)||Midterm and Industry Talk|
|Week 7 (3 Oct)||Bias and Variance and Overfitting|
|Week 8 (10 Oct)||flipped VC Analysis, Regularization and Validation|
|Week 9 (17 Oct)||Decision Trees and Ensemble Methods|
|Week 10 (24 Oct)||Unsupervised Learning|
|Week 11 (31 Oct)||flipped Neural Networks|
|Week 12 (7 Nov)||Deep Learning Architectures and Revision|
|Week 13 (15 Nov)||Three Learning Principles and Ethics|
|Final Assessment: 25 Nov (Sat), 9:00-11:00. Venue: Updated Seminar Room 1 (SR1; COM1 #02-06)|