![]() Norms, symmetry, positive definiteness, eigen-decomposition. Matrices, vectors, Lp norm, geometry of the Machine learning topics that I believe every engineering student should be Given the variety of materials in the literature, I have distilled a set of four fundamental Point that they can carry over to their research/industry problems. Purdue ECE graduate students areĪlso very solid in mathematics (Well, at least this is what I demand ourĬommunication, Networking, Signal and Image Processing students). Important than effcieint programming skills. These students, big pictures and connections across different topics are more Interested in physics and intuitions than programming per se. ![]() Engineering students areĭifferent from computer science students, in the sense that they are more Mathematical background to appreciate the depth. Students with sufficient exposure to engineering problems, and have enough It is a uniquely designed machine learningĬourse for Purdue graduate students. Machine learning course, focus on the big pictures, and do something relevant So I am seeing a need forĮngineering students, like ours at Purdue ECE. Students, the content may appear abstract. Great courses in some of our peer institutions are sometimes Students who have taken these courses can only speak the jargon but cannot doĪny actual work. ![]() Many so-called data scienceĬourses on online platforms are more or less bubbles with no real content. Quality variation from one source to another. However, if we go around the internet, it is indeed quite shocking to see the Needless to say, there is a tremendous demand for machine learning nowadays. Is already available on the internet (and other institutions). ![]() When IĬreated the course in 2018, my vision is to do something different from what This is a graduate-level machine learning course at Purdue ECE. Residential students please take Spring 2024. ![]()
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