Additional Resources for ECE 435 - Machine Learning and Pattern Recognition

Probably the most important class that you’ll take as anyone working with data.

What is ECE 435?

The course name Machine Learning and Pattern Recognition is a very vague notion. In concrete terms, this course is a graduate-level (no really, it’s cross listed as ECE 535 and majority graduate students) proof-based data-driven machine learning course.

When Should You Take It?

As soon as possible, as long as you have a solid grasp of linear algebra, multivariable calculus, and probability (whether or not you have actually taken those courses). If you want to take courses, I would recommend MAT 217, MAT 201, ORF 309 for requisite knowledge, but that might be overkill. I say take this course as soon as possible because a solid mathematical foundation of data-driven machine learning algorithms will make all the concepts much, much more clear and allow you to apply these skills anywhere.

You may think that you understand ML from a COS 324-style hand-wavy machine learning course, but I didn’t, and you don’t.

Additional Resources

My Advice and Notes

To Be Added post-completion

Tejas Gupta

New York City, USA
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Tejas Gupta is a Princeton University student in the Department of Computer Science. He is currently studying at ETH Zürich.