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These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.

Jupyter Notebook 100.00%

vmls-companions's Introduction

VMLS-Python-and-Julia-Companion

*This is a companion to the Julia companion for: "Vectors, Matrices, and Least Squares" by Boyd and Vandenberghe. Which you can find here: http://vmls-book.stanford.edu/.

You can find notebooks with implementations in both Python and Julia that are direct references to the companion.

This is best perused in conjunction to the first degree companion: http://vmls-book.stanford.edu/vmls-julia-companion.pdf.

You can also find a Python companion put together by Leung and Matyspura here: https://ses.library.usyd.edu.au/handle/2123/21370

To run Julia in a jupyter kernel, Julia offers documentation here: https://pkg.julialang.org/docs/IJulia/nfu7T/1.9.3/. Also note that if you use brew as a primary package manager connected to your kernels, it will automatically setup the kernel for you when you run brew cask install julia.

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vmls-companions's Issues

Chebyshev bound function

According to VMLS:
cheb_bound = lambda x,a: npl.norm(x)**2//a**2

But in python companions，the denominator is not squared:
cheb_bound = lambda x,a: npl.norm(x)**2//a

Is this a mistake?

Minor question

I just want to be sure that the notebooks are exactly equal to the Julia companion pdf that is cited in the README.

Thanks.

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