Robust and Scalable Systems

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Related lectures (30)

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Independence Polynomial of Dependency Graph

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

Dense Graphs: From Theory to Applications

Explores the transition from sparse to dense graphs and their real-world applications.

Graph Theory and Network Flows

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Graph Algorithms: Memory Management and Traversal

Explores memory management, graph representation, and traversal algorithms in Python, emphasizing BFS and DFS.

Graph Machine Learning

Delves into graph-enhanced machine learning, focusing on fraud detection, malware detection, and recommendation systems.

Graph Algorithms: Modeling and Representation

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Sparsest Cut: Leighton-Rao Algorithm

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

Handling Network Data

Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.

Irreducible Matrices and Strong Connectivity

Explores irreducible matrices and strong connectivity in networked control systems, emphasizing the importance of adjacency matrices and graph structures.

Neural Signals and Connectomes

Explores neural signals, connectomes, graph theory, and multi-voxel pattern analysis in fMRI trials.