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Data Mining

This note covers the following topics: Introduction, inductive learning, Decision trees, Rule induction, Instance-based learning, Bayesian learning, Neural networks, Model ensembles, Learning theory, Clustering and dimensionality reduction.

Author(s): Pedro Domingos

NA Pages

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Database Systems Lecture Notes

This note is designed to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, query optimization, query processing, and transactions. Topics covered includes: The relational model, Schema design, database internals, Database operators and query processing, Indexing and access methods, Buffer pool design and memory management, Join algorithms, Query optimization, Selinger optimizer, Transactions and locking, Optimistic concurrency control, Distributed transactions, Parallel databases, Scientific databases, NOSQL , ORM, DryadLINQ, Streaming databases, database as a service.

Author(s): Prof. Samuel Madden, Prof. Robert Morris, Prof. Michael Stonebraker, Dr. Carlo Curino

NA Pages