Lectures related to Efficient Graph Queries: Memory Constraints

Introduces relational query languages, focusing on algebra operators and query optimization.

Graph Neural Networks: Interconnected World

Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.

Mathematical Analysis: Functions and Composition

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

Belief Propagation in Random Graphs

Explores belief propagation in random graphs and Bethe free entropy.

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Query Operators: Part 1

Explores query processing steps, physical plans, pipelined execution, and hashing for projections and joins.

Information Retrieval Indexing: Part 2

Explores constructing an inverted file for information retrieval indexing and the map-reduce programming model.

Graphs: Properties and Representations

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Handling Data: Intro to Pandas

Introduces the fundamentals of handling data, emphasizing the importance of Pandas and data modeling for effective analysis.