Johns Hopkins University 3 credits Applied Mathematics & Statistics
The course, an introduction to the foundations of large language models, is a coherent mix of theory and practice. Topics include: Empirical Risk Minimization, Gradient methods (GD, SGD, Adam, etc), Language Models Architectures (Transformers, State Space Models), Scaling Theory.
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