Star cluster

Related lectures (32)

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Covers space, stars, the solar system, nebulae, and galaxy clusters.

Covers the Stochastic Block Model for community detection, focusing on the detection of communities, clusters, and groups.

Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

Covers stellar evolution, fusion processes, and the age of stellar clusters, emphasizing gas pressures and star evolution based on mass.

Explores the birth, life, and death of stars, including fusion processes and white dwarf formation.

Covers the architectures for parallel databases, including Shared Memory, Shared Disk, and Shared Nothing.

Explores clustering in high-dimensional space, covering methods like hierarchical clustering, K-means, and DBSCAN.

Covers satisfiability threshold, clusters of solutions, parameter alpha, and average cluster computation.

Covers the K-means algorithm for clustering data samples into k classes without labels, aiming to minimize the loss function.