numpy
resourcesNumPy stands for Numerical Python. It’s widely used in Linear Algebra applications and has become a de facto library for use in Machine Learning. It uses memory efficiently and is mostly implemented in C, thus is a very efficient option for numerical calculations (see more in Reference #3 by Sebastian Raschka). I’ve made a list of resources for the numpy
library to help someone new or someone in need of a good reference later on. It was created by Travis Oliphant in 2005 (also the creator of SciPy). The package lives on GitHub (Link).
scipy
docs. Short, but good starting point. Refnumpy
by Jake VanderPlas. Refnumpy
by Tirthajyoti Sarkar. NotebookLinear Algebra Review (Andrew Ng).
Exercise: Follow along with these courses by doing things concurrently in numpy
.
There are likely many more great resources out there so feel free to create an issue on this GitHub repo letting me know about yours or others.