Margot Gerritsen
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Professor
Stanford University |
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Margot Gerritsen is a Professor at Stanford University and co-founder and co-director of WiDS Worldwide. Her expertise is in computational mathematics. She is particularly fond of computational fluid dynamics and linear algebra. Margot received her MS from TU Delft and her PhD from Stanford. Prior to her position at Stanford, she spent five years as a faculty member at the University of Auckland, New Zealand. Margot was born and raised in the Netherlands and left the flat lands in 1990 in search of hillier and sunnier places. She still has her Dutch accent. She currently lives in the Oregon mountains with her partner Paul.
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Workshop: What would we do without Linear Algebra, part II: Diving Deeper into the Singular Value Decomposition
May 26, 2021; 8:00-9:15 am PST
May 26, 2021; 8:00-9:15 am PST
Prerequisite: We will assume that you are familiar with the vector and matrix algebra discussed in part I (see below).
This is the second of our workshops devoted to linear algebra, which forms the foundation of many algorithms in data science. In part I of the series we introduced vector and matrix algebra, and briefly looked
at the intriguing and ever so useful Singular Value Decomposition (SVD). In this workshop, we will take a deeper into the SVD. We will explain how it is derived, how it can be computed, and also how it is used.
This is the second of our workshops devoted to linear algebra, which forms the foundation of many algorithms in data science. In part I of the series we introduced vector and matrix algebra, and briefly looked
at the intriguing and ever so useful Singular Value Decomposition (SVD). In this workshop, we will take a deeper into the SVD. We will explain how it is derived, how it can be computed, and also how it is used.
Workshop: Linear Algebra, Part I: What Would We be Without It
March 8th & June 30, 2021; 8:00-9:15 am PST
March 8th & June 30, 2021; 8:00-9:15 am PST
Prerequisite: Basic algebra
Linear algebra forms the foundation of many algorithms in computational mathematics and engineering, and data science is no exception. In this workshop we explore the beauty and power of linear algebra, and discuss the most critical linear algebra concepts and algorithms used in data science. Consider this workshop a first exploration of linear algebra foundations and an appetizer for more.
Linear algebra forms the foundation of many algorithms in computational mathematics and engineering, and data science is no exception. In this workshop we explore the beauty and power of linear algebra, and discuss the most critical linear algebra concepts and algorithms used in data science. Consider this workshop a first exploration of linear algebra foundations and an appetizer for more.
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