Problem Sets & Exams
Here is a tentative list of problem set topics. The topics
may change a bit and there may be a 8th problem
set but we hope to stay with this schedule. As problem sets are released,
more information and resources will be added below.
Problem Set 0: Review
This homework is not graded.
Release: 01/18 Due: None
Problem Set 1: Introduction to Machine Learning
Release: 01/27 Due: 02/03
Problem Set 2: Learning Decision Trees
Release: 02/03 Due: 02/15
Problem Set 3: Online Learning (hw3.pdf)
Release: 02/15 Due: 02/27
- A zip file with all relevant files:
It contains these files:
python/gen.py, python/add_noise.py. The
data generation files are introduced
in the pdf file.
- Source file: hw3.tex, cs446.tex
Use the latex code for the tables in hw3.tex file to report your results, note that you will also
need cs446.tex to compile it
- Solution: hw3-solution.pdf
Problem Set 4: Kernels, SVM, Learning Theory, Boosting (hw4.pdf)
Release: 02/28 Due: 03/11
You may not use late credit for this problem set.
The solution will be released the morning of 03/12. The submission site will be opened until 03/11 11:59 PM.-->
Problem Set 5: Neural Networks, Multiclass Classification (hw5.pdf)
Release: 03/31 Due: 04/11
Problem Set 6: Probabilistic Models (Naive Bayes)
Release:04/12 Due: 04/20
Problem Set 7: Expectation Maximization and Learning Probability Distributions
Release: 04/20 Due: 05/01
You can use NO late credit hours for this problem set. The submission channel will be closed at 11:59 pm.