Category Theory in ML
Dan explores the applications of category theory to machine learning, emphasizing its focus on behavior rather than strict axioms. This perspective can lead to innovative ways of extending and designing algorithms, particularly in clustering and manifold learning. By framing machine learning components through this lens, new insights into the structure and transformation of algorithms emerge, bridging the gap between theoretical concepts and practical applications.In this clip
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