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Theoretical machine learning/deep learning is an important yet often ignored subfield of AI/ML that drives the intuition behind many powerful AI model design choices. In this discussion, we introduce topics like PAC learning, neural network initialization analysis, and neural network gaussian process results and tie them back to their practical use cases!
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