[jimmy_dean]

The machine learning Stanford courses are probably the best open education contributions I've encountered. From Ng's CS229 material to Karpathy's rendition of CS231n. These are some of the best pedagogical materials on machine learning/deep learning available.

[discordance]

Unfortunately the videos for this course won't be made available until after the course has finished.

[_cs2017_]

https://youtu.be/8rXD5-xhemo

[mark_l_watson]

Thanks for the link, just subscribed.

Years ago I took Chris Manning and Dan Jurafsky‘s Coursera NLP class and it was excellent. I also own, I think, every book they have written including Jurafsky’s book on food.

It is extremely generous of top universities to make their classes available online. Of course, watching the videos and trying the homework assignments on one’s own is not the experience of going to Stanford, but it is less expensive!

[ivansavz]

Thx. This seems to be part of a playlist of 2019 lectures:

https://www.youtube.com/watch?v=8rXD5-xhemo&list=PLoROMvodv4...

[bitforger]

I still remember Nick Parlante's Intro to CS. Great stuff.

https://lagunita.stanford.edu/courses/Engineering/CS101/Summ...

[jimmy_dean]

Yup! I made heavy use of his codingbat material during 1st year.

https://codingbat.com/java

[ai_ja_nai]

True at heart, I am totally in love with CS231 (Yeung and Johnson)

[jimmy_dean]

That course is really the best blend of theory and application. I find their approach more tasteful than fast.ai's, but to each their own!