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Deep Representation Learning & Approximation Theory →0/5
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Lecture 01: Introduction to Deep Learning (6.7960)

Sara Beery · 1:00:51

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Lecture 02: How to Train a Neural Net (6.7960)

Sara Beery · 1:19:34

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Lecture 03: Approximation Theory (6.7960)

Jeremy Bernstein · 1:22:42

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Lecture 1: SQL Optimization Background (15-799)

Andy Pavlo · 53:57

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Lecture 2: History of Query Optimizers ft. IBM System R (15-799)

Andy Pavlo · 1:10:40

Lecture 1: SQL Optimization Background (15-799)

Andy PavloCarnegie Mellon University

Professor

53:57·2025·graduate level
Path step 4: Establishes declarative query optimization as search over equivalent relational algebra plans.

This lecture establishes fundamental concepts of relational database query optimization, including algebraic transformations and the role of cost-based optimizers in enhancing query performance.

Systems & CSDatabase SystemsSQL OptimizationRelational DatabasesQuery Processing

Andy Pavlo (https://www.cs.cmu.edu/~pavlo/)

Slides: https://15799.courses.cs.cmu.edu/spring2025/slides/01-background.pdf

15-799 Special Topics in Database: Query Optimization (Spring 2025)

Carnegie Mellon University

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Lecture 03: Approximation Theory (6.7960)

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Lecture 2: History of Query Optimizers ft. IBM System R (15-799)

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