Learning the intricate concepts of linear algebra from scratch
Working knowledge of various linear algebra techniques using Python
A visual understanding of concepts such as vector space, spans, and subspace with animations
Familiarity with valuable concepts like fields, eigenspaces, diagonalization, and SVD
An understanding of how linear algebra concepts build the most useful tools in data science, such as neural networks
The ability to apply linear algebra concepts to real-world problems through coding exercises and practical projects
Linear algebra is a fundamental pillar of data science. In advanced models in data science, like neural networks, the inputs and transformations are based upon vectors, matrices, and tensors which require a reasonable understanding of linear algebra to get the desir...
Solving Linear Systems
Linear Regression and Least Squares
Vector Spaces of a Matrix
Singular Value Decomposition: SVD
Learning to Find Discriminative Null Space for Face Recognition
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