Glad you found the video useful! :) I'd like to create more videos this year, so please stay tuned.

Thank you! I used to do private tutoring while I studied at university, so I guess I miss explaining this stuff :D Teaching is a good way of learning, nothing quite makes you understand a subject like having to break it down for someone else. Your videos have a nice easy-to-understand presentation and great visuals, I'd love to see your take on some more advanced topics! I'm sure you'll get there in time :)

Thanks, I'm glad it was helpful :)

Glad it was useful! I have something in the works on Levenshtein automata and Tries, that video is coming :)

Thanks! It's Jupyter Notebook with github.com/dunovank/jupyter-themes and some custom CSS styles on top using github.com/openstyles/stylus

@@BigPython Thank you very much!

@@BigPython I played with the styles a little bit, and figured, that you were using the grade3 style. However my understanding of the openstyles, that is has to applied to the browser itself. Is that correct? Do you mind sharing your style?

@@lammelmiklos3765 Yes, it's applied at the browser level. I've added my current CSS to the git repo, feel free to have a look :) github.com/tkarabela/bigpython/blob/master/jupyter-grade3-bigpython.css

Thank you! :)

In the Wagner-Fisher algorithm, when computing d[i, j] you take minimum of the neighbors d[i-1, j], d[i, j-1], d[i-1, j-1] with cost of the operation added to each. Usually all the costs (weights) are set to 1, except for the case of d[i-1, j-1] when a[i-1] == b[j-1] (which is a match, so it should not add to the distance).