jupyter-guide-to-linear-algebra
The Jupyter Guide to Linear Algebra covers many of the core topics that would appear in an introductory course on linear algebra, together with several applications. The guide also provides a brief introduction to Python, with focus on the portions that are relevant to linear algebra computations. The Jupyter Guide to Linear Algebra should prove useful to students in a traditional first-year university course on linear algebra.
Features:
- Development of a module to be used along side of the Jupyter Guide to Linear Algebra, or independently.
- Exercises aimed at exploring linear algebra concepts, as well as exercises to practice writing Python code.
- Instruction on the basic use of NumPy, SciPy, and Matplotlib.
- Introduction to Hill ciphers, Markov processes, least squares solutions, and other applications of linear algebra.