Computation of t_p, f_p, t_n (threshold detection in week 1, lab2 , exercise 2)

That’s great news, @Juergen_Geiser!

Good observations, too. The “fast coding” techniques you point out are ways to operate on a whole array or matrix, rather than looping through and operating on each value individually. Vectorized approaches like this typically run faster, in addition to being more concise. These come in very handy for machine learning where we use lots of matrices of data (tensors, arrays, …).

I don’t have any favorite book or online references for summarizing these types of techniques, but try googling something like “array operations python tips and tricks” or “python vectorization” to see what you find. Here’s one Medium article I noticed:

Also, check out the MLS Resources category which has a whole range of helpful info for learners in this course. You may find some useful python recommendations there. And, it’s generally a good resource to know about. You can either search for keywords at the main MLS Resource level, or go to the FAQ page and drill into whatever looks interesting or helpful from there.