MIT – Machine Learning with Python-From Linear Models to Deep Learning

I am participating as reviewer of this Masacchuset Inistitut of Technology course. I always admired this university as one of the best in the world. For me it was always unrecheable to study in USA, but thanks to coronovirus time, I discovered that they lead free courses on different topics. As my recent interest is Artiffical Intelligence, I took this course as well as free summer school of AI on Technical University in GDN.

I will focus on this MIT course. This is not the easiest course – the first „warmup” sessions, forced me to remind myself all algebra, differntites and integrals, probablisitic theory, vector and matrixes calculations. I must admit that it was hard first week. Now the topics are more related to Machine Learning and this tutor is just excelent – he explains everything as for 5-year old kid, so even me, who used higher math during my studies almost 18 years ago, can understand everything in English without much checking Polish sites related to this topics.

Here are all lectures from this course:

https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006/lecture-notes/

Here is very useful repo reg. to this project:

https://github.com/dnackat/mitx-6.86x-machine-learning/tree/94e47c7ca834a69cca13da151e85bd6b192a3da0

For sure I will take other courses from this domain on MIT. My goal is to improve my robot for next Baltic Robbo Battles.

If you have time – just participate in one of them – as it is really worth it!

2 myśli na “MIT – Machine Learning with Python-From Linear Models to Deep Learning

  1. Hi there to aⅼl, how is the whole thing, I think every one is ցetting more from thiѕ web page,
    and your views are pleаsant in favor of new visіtors.

  2. Very great post. I just stumbled upon your weblog and wanted to mention that I’ve reаlly loved surfing around your blog posts.
    In any case I’ll be subscriЬing in ʏour fеed and I
    am hoping you write once more very soon!

Dodaj komentarz

Twój adres e-mail nie zostanie opublikowany.