printer friendly pageCME 103: Introduction to Matrix Methods (EE 103)
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.
Terms: Aut, Sum
|
Units: 3-5
|
UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
|
Grading: Letter or Credit/No Credit
Instructors:
Jani, T. (PI)
;
Osgood, B. (PI)
;
Degleris, A. (TA)
;
Harvey, B. (TA)
;
Jani, T. (TA)
;
Landy, N. (TA)
;
Muppidi, S. (TA)
;
Shen, H. (TA)
;
Sowell, S. (TA)
EE 103: Introduction to Matrix Methods (CME 103)
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.
Terms: Aut, Sum
|
Units: 3-5
|
UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR
|
Grading: Letter or Credit/No Credit
Instructors:
Jani, T. (PI)
;
Osgood, B. (PI)
;
Degleris, A. (TA)
;
Harvey, B. (TA)
;
Jani, T. (TA)
;
Landy, N. (TA)
;
Muppidi, S. (TA)
;
Shen, H. (TA)
;
Sowell, S. (TA)
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