Clustering and Dimensionality Reduction
Use worked k-means and PCA examples to distinguish discovering groups from compressing representations, and explain the limits of distance, scaling, and visualization.
Use worked k-means and PCA examples to distinguish discovering groups from compressing representations, and explain the limits of distance, scaling, and visualization.
Follow text through token IDs, embeddings, and contextual states, distinguishing tokenization, position, padding, and retrieval vectors.