What are the prerequisites for the class?

See here.

Will undergraduate and graduate students be graded differently?

Yes. Graduate students will be asked to do more work (e.g. extra questions in homeworks and/or exams). And grad and undergraduate students will be curved differently.

I am not comfortable using LaTeX. Can you help?

LaTeX is extremely useful for writing mathematics. While teaching LaTeX is beyond the scope of this course, there are some online resources that can help. Overleaf is an online LaTeX editor and has well written documentation on getting started with LaTeX.

Which languages should we use for the programming assignments?

See the instructions for programming assignments.

For the programming assignments, should I turn in source code or will compiled binaries do?

We will not accept compiled binaries. We need to see the source code. If you submit a compiled binary without the source code, we will not grade it.

No. The goal of the homeworks is to help you learn about the intricacies of implementing learning algorithms and conducting experiments with them. So you can’t use libraries that do this work for you.

For example, you cannot use decision tree code from scikit learn or SVM from Weka, logistic regression from TensorFlow, etc. You should implement all the machine learning algorithms (and experiment related code like cross-validation).

How do I get access to the CADE machines?

The CADE lab website should give all the information you need. See the sidebar on that page for useful links.