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Major: Chemistry
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Published:
c/o 2024, Chemistry
The hero of today’s story will be a matrix. The “villain,” a system of linear equations. This talk will introduce the audience to two ways of solving a linear system of equations using matrix-vector notation. We also introduce the concept of an eigenvalue $(\lambda_i )$ and eigenvector $(\vec{v}_{\lambda})$ though we omit any explanation for a systematic way to find them. Equipped with this knowledge, we will present readers a few simplified models to display the real-world utility of these concepts.
Published:
c/o 2024, Chemistry
Building off of my first talk, I will couple linear algebra and calculus to introduce the idea of the cost function along with the simple technique of linear regression. We’ll then revisit eigenvectors and values while briefly describing how to systematically find them. The Google Page Rank algorithm will also be shown again, this time with the numerical calculations of finding the eigenvector associated with $\lambda = 1$. From there, we’ll touch on the singular value decomposition (SVD), one of the most important linear algebraic tools given its utility for dimensionality reduction and look at image compression using the technique.
Undergraduate course, University of Virginia, Chemistry, 2023
TA: Serena Mardini
Undergraduate course, University of Virginia, Chemistry, 2023
TA: Mohan Shankar
Undergraduate course, University of Virginia, Chemistry, 2023
TA: Someone