[Puer]

I agree. I hope that M.I.T. is able to consolidate these domains in a cohesive manner. The mathematics of ML is super unfriendly because it borrows from so many inter-related domains. You'll end up with notation that uses sigma to represent both summation and covariance within a single expression, or inconsistencies with whether vectors are column vectors by default or row vectors. It makes your understanding of the material dependent on whether you had the same background as the author.

[Koshkin]

In mathematics, good and consistent notation does help learning stuff; but I noticed that it can also have some sort of "parasitic" effect and interfere with the true understanding of things, and so I find it useful to try and see if I can understand something given a less elaborate notation (or without one at all).

In general, one has to remember that mathematical notation was invented to make calculations (on paper) more efficient and not with the goal of making it easier to understand things.