Modern Linear Algebra Using Python Instead of a Textbook

Overview

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This course teaches linear algebra concepts using Python instead of a textbook. Students will learn matrix operations, LU decomposition, matrix inversion, null space, Ordinary Least Squares, QR decomposition, and the basics of the Jacobian for neural networks. The course focuses on practical implementation using the sympy library. The intended audience for this course is individuals interested in learning linear algebra through hands-on Python programming.

Syllabus

Linear algebra using sympy.
Matrices in python using sympy.
Matrix arithmetic using sympy.
LU decomposition of a matrix using sympy.
Inverse of a matrix.
Null space of a matrix using sympy.
Ordinary Least Squares Tutorial using Python.
Gram Schmidt process for QR decomposition using Python.
Basics of the Jacobian and its use in a neural network using Python.