EdusalsaDiscover Your Stanford

- autumn
- spring

3 - 5 units

Letter or Credit/No Credit

Introduction to applied linear algebra with emphasis on applications. Vectors, norm, and angle; linear independence and orthonormal sets; applications to document analysis. Clustering and the k-means algorithm. Matrices, left and right inverses, QR factorization. Least-squares and model fitting, regularization and cross-validation. Constrained and nonlinear least-squares. Applications include time-series prediction, tomography, optimal control, and portfolio optimization. Undergraduate students should enroll for 5 units, and graduate students should enroll for 3 units. Prerequisites:MATH 51 or CME 100, and basic knowledge of computing (CS 106A is more than enough, and can be taken concurrently). EE103/CME103 and Math 104 cover complementary topics in applied linear algebra. The focus of EE103 is on a few linear algebra concepts, and many applications; the focus of Math 104 is on algorithms and concepts.

GER:DB-Math

WAY-FR

WAY-AQR

## LEC

Tuesday Thursday 9:00:00 AM - 10:20:00 AM @ Hewlett Teaching Center 200 with Neal Patel Logan Spear Sean Chang Reese Pathak Trisha Jani Sofia Jimenez Stephen Boyd Mark Nishimura David Tse Anthony Degleris Govinda Kamath Caitlin Go Jonathan Lin Guillermo Angeris Juliet Daniel John Sholar Lucy Li

## LEC

Tuesday Thursday 10:30:00 AM - 11:50:00 AM @ Hewlett Teaching Center Rm 101 with Brad Osgood

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**Pranav Rajpurkar** is a PhD student in Computer Science at Stanford, working on Artificial Intelligence for Healthcare. He was previously a Stanford undergrad ('16).

**Brad Girardeau** got his B.S, M.S. degrees in computer science at Stanford ('16, '17). When not thinking about computer security, he can be found playing violin or running across the Golden Gate Bridge.

## Discussion

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