Deep Learning Alchemy
Lecture
Main Campus
Course Description
Deep learning is now the foundation of all of machine learning and AI, making it more important than ever for students to obtain mastery of the empirical phenomena and experimental skills involved in deep neural networks. How can students acquire the skills necessary to invent the next generation of architectures or develop new broad theories of how deep learning works? This course takes the stance that knowledge or math abilities alone are not enough, and there is no substitute for getting your hands dirty and running many, many experiments. To this end, we will work through computationally tractable domains and take students through the process of obtaining mastery in this domain through efficient experimentation and experiment outcome prediction. More details can be found at https://deep-learning-alchemy.github.io/
CS 312
Units: 3–5
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Typically Offered
Not Available
Grading Basis
Letter or Credit/No Credit
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
