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This course will cover theory and practice of deep learning, including neural network and structured models, optimization algorithms, and applications to perception and artificial intelligence In this course, students will learn the fundamental principles, underlying mathematics, and implementation details of deep learning. I think this is an interesting class with quite well organized lecture, reading materials and assignment.
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I want to say this is one of the best omscs course With the recent advances in large language models (llms), successful commercial deployments of these techniques continue to grow I have thoroughly enjoyed this course and my knowledge in the topic increased many folds
Other omscs courses should be like this
Every assignment included coding, analysis and a paper review It was very comprehensive to know all about the topic. N this course, students will learn the fundamental principles, underlying mathematics, and implementation details of deep learning. Given the recent rise of llms, i decided to switch the order of my courses and take deep learning as soon as i can (i originally intended to do machine learning first).
Modules will be presented via instructor lectures and reinforced with homeworks that teach theoretical and practical aspects The course will also include a project which will allow students to explore an area of deep learning that interests them in more depth. It largely follows the curriculum of similar deep learning courses like cs231n from stanford, going through the evolution of deep learning through computer vision lens. Cs 7643 at georgia institute of technology (georgia tech) in atlanta, georgia
