Introduction to Linear Algebra for Data Science

Explore the fundamental concepts of linear algebra and their applications in data science through this 41-minute webinar from the Data Science Festival Summer School 2021. Delve into key topics such as linear combination, vector representation, dot product, matrix decomposition, and matrix factorization, with real-world examples including text similarity, image representation, data visualization, and content recommendation. Gain insights into why linear algebra is crucial for data science, its role in regression, vector and matrix representations, and when non-linear methods are necessary. Ideal for data science practitioners seeking to enhance their understanding of core algorithms and documentation through a solid foundation in linear algebra.

Intro
Finding similar texts
Weight vectors
Norm, angle and similarity
Other things that are matrices
Matrix decomposition