Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Graph database

Related lectures (30)

Covers the Stochastic Block Model for community detection.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores finding the equation of the tangent line to a function's graph at a point.

Explores the diagonalization of matrices and the conditions for exact diagonalization, with examples demonstrating the process.

Explores the properties and applications of Cayley graphs in group theory and network analysis.

Explores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.

Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Covers data wrangling techniques using Hadoop, focusing on row versus column-oriented databases, popular storage formats, and HBase-Hive integration.

Covers the origins and types of NoSQL databases, focusing on MongoDB and CRUD operations.

Covers the Ising simulation, focusing on update methods and measurements.

Discusses the graph of a relation and the concept of separation.

Explores counterfactuals in SEMs and D-Separation in graphical models.

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Explores the for notation for querying databases using examples with a mini-database of books.

Covers graph processing with a focus on Oracle Labs PGX, discussing graph analytics, databases, algorithms, and distributed analytics challenges.

Explores the ubiquity of graphs in modern data and analytics, focusing on the shift in organizations' perception of graph technologies.

Covers the analysis of functions, composition, and mathematical induction.

Explores learning from interconnected data using graphs, covering challenges, GNN design, research landscapes, and democratization of Graph ML.

Explores concurrent programming theory and practice, covering system models, cache coherence, and graph processing.