This workshop briefly introduces participants to concepts in basic linear algebra and proceeds to discuss matrix computations and algorithms that underlie data science and computational engineering. Upon completion, participants will have an understanding of what is behind black box software packages and be able to make more informed decisions about what type of algorithm may be best for a given application. After familiarization with basic matrix and vector operations, the workshop discusses the foundational concepts on which many algorithms used in data mining, machine learning and deep learning are built. Examples include solving linear systems, eigenvalues and eigenvectors, and factorizations. Exercises help participants apply concepts to problems in optimization, machine learning and statistics.
Recommended background: knowledge of vector calculus.
- Basics: matrices, vectors and fundamental operations: products, norms
- Solving linear systems
- Least squares
- Eigenvalues and eigenvectors
- Fundamental factorizations: QR, tall-skinny QR, SVD
To view other workshop descriptions, or to get general information about the 2016 ICME Summer Workshop Series, click here.
ICME Summer Workshops are open to participants 18 years and older. If you are under the age of 18 and would like to participate, please contact firstname.lastname@example.org.
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