(Stay tuned, as I keep updating the post while I grow and plow in my deep learning garden:))
This page provides useful resources about Linear Algebra basics for Data Science, AI, ML and DL.
- The lecture notes paper by Prof. Petros Drineas (Purdue University) and Prof. Michael Mahoney (UC Berkeley) — especially Section 2 in the paper
Drineas, P., & Mahoney, M. W. (Dec 24, 2017). Lectures on Randomized Numerical Linear Algebra. arXiv preprint arXiv:1712.08880. (pdf)
- Machine Learning – 03. Linear Algebra Review (YouTube playlist, 6 videos)
- Linear Algebra for Machine Learning (by on December 24, 2014 in Start Machine Learning)
- Python Introduction and Linear Algebra Review (2017, Stanford, pdf) – used Python 2.7
- Linear Algebra and Python Basics (2017) – pdf
- Python Tutorial: NumPy Matrix and Linear Algebra (2017, Bogotobogo, pdf)
- Linear algebra explained in four pages (pdf)
- basic linear algebra with Python (GitHub repo, the main ipython notebook)
- Scipy Tutorial: Vectors and Arrays (Linear Algebra) – 2017
- A comprehensive beginners guide to Linear Algebra for Data Scientists (2017)
- Linear Algebra with Python (2013)
- TBA
