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ai deep-dive Reading Stanford CS229

Clustering and k-Means: A First Alternating-Optimization Algorithm

Chapter 10 introduces unsupervised learning through k-means: alternating updates make distortion non-increasing and numerically convergent, but do not guarantee a global optimum.

#cs229#machine-learning#unsupervised-learning#clustering#k-means
learning guide Reading CMU 10-301 Machine Learning

CMU 10-301 HW9: Close the Course with Ensembles, k-Means, PCA, and Recommenders

The final written assignment combines ensembles, clustering, representation, and recommendation to test whether you can choose a learning paradigm from problem structure.

#cmu#machine-learning#clustering#pca#recommender-systems