Every time I keep repeating myself I feel the urge to write things down so that I can simply point such resource in future occasions. Every semester I start my course showing a collection of visual resources for priming my students’ mental picture muscle. By the end of the semester, they are usually able to see a little more.

Everything I teach

Previous edition of my courses can be found under didactics. I teach from primary and middle schoolers, to PhD students, to retired folks. From maths, science, and programming to music, dancing, and cooking.

From my (former) high-school inter

Vivek put together these two manims for me:

  1. The Neural Network, A Visual Introduction and
  2. What happens inside a neural network?

Searching Twitter

To know my (or others’) thoughts on SVD search for (from:alfcnz) SVD on Twitter.
Other examples:

  • (from:alfcnz) linear algebra
  • (from:alfcnz) probability data science

If you become a follower, you’ll be automatically notified with new learning visual content.

Maths

Is your maths a little rusty? No problem. Check out Marc’s book Mathematics for Machine Learning. You really want to read Chapter 5, Vector Calculus, before homework 1.

Linear algebra

Please, binge watch Essence of Linear Algebra by Grant. This is a requirement.

For a more in-depth coverage of the topic, I like Gilbert’s Introduction to linear algebra and corresponding video lectures.

Trefor

His YouTube channel is worth your subscription. Full playlists for discrete maths, linear algebra, calculus I-IV, and differential equations.

Eigensteve

Do you need to brush up control? Check out Control Bootcamp. Additional playlists include differential equations and dynamical systems, complex analysis, vector calculus and partial differential equations, and singular value decomposition. Steve’s YouTube channel is full of extremely well done lectures.

Blogs

Shameless plug

Do eigenvectors need to be orthogonal? (You keep giving me the wrong answer. Yann included…)
May be worth checking out Eigen-stuff.

Gregory

His blog is stellar. I recommend particulary:

  1. Singular Value Decomposition as Simply as Possible and
  2. A Geometrical Understanding of Matrices.

Network drawing software

Draw.io is what I use to draw my slides’ diagrams with. It could be a useful tool for you too.

TikZ

Yet, for my textbook I’m using $\TeX$-based TikZ. Why? Because I’m crazy. Another aspect is that, being text, you can edit it any time, apply whatever theme you want, and the maths in the figures will be updated if I change any definition in the preamble. Moreover, I can draw parametrised figures, where lengths and sizes are the result of computations.

Similarly, all plots are also $\TeX$ generated with PGFPlots. Yes, it’s a bit painful at the beginning, but the final quality is extremely satisfying. In fact, all plots in my textbook are drafted with Matplotlib and then recreated with PGFPlots, which reads some ASCII files, where I’ve dumped the data points.