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Is it just me that doesn't like these stanford offerings? I find it very, 'to the point' kind of teaching, AI and ML. I prefer to watch Profs teach to a live au

Is it just me that doesn't like these stanford offerings? I find it very, 'to the point' kind of teaching, AI and ML. I prefer to watch Profs teach to a live audience. They normally fill a sense of energy in live classes. The style of teaching in lumps of 5-6 mins on youtube is very boring. And also the assignments here lack a serious effort compared to their original offerings. I started my learning way back with http://www.cs50.net http://www.cs50.net. I thought it would be great watching ai-class.org, but it isn't. Anyway, I found a very good AI course from UC-Berkeley (CS188). It's a streaming of live class sessions and is very interesting. And the assignments are top-notch as they are original class room psets. It would be great if the videos are sessions to live audience.

dlo 15y ago
Here are the classroom lectures for ML. http://classx.stanford.edu/ClassX/system/users/web/pg/view_subject.php?subject=CS229_FALL_2011_2012&cxm=1 http://classx.stanford.edu/ClassX/system/users/web/pg/view_s...
- dlo 15y ago
  Also, the classroom lectures for the upcoming algorithms course are already up. http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=IntroToAlgorithms http://openclassroom.stanford.edu/MainFolder/CoursePage.php?...
- sravfeyn 15y ago
  Thank you !Is there the original AI class too?
- NnamdiJr 15y ago
  Thanks a lot for the link. Good way to review and compare with online class.
ot 15y ago
I didn't like Ng's course on ML too much, it is very good if you just want to implement the algorithms, but it gives no insight on why they work. I enjoyed far more Tom Mitchell's lectures, they gave me a much better understanding of the algorithms described: http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml There are some comments on HN about it http://news.ycombinator.com/item?id=3199718 http://news.ycombinator.com/item?id=3199718
- sravfeyn 15y ago
  great! Thanks. I am actually already following ML from Harvard. http://www.seas.harvard.edu/courses/cs181/extension/ http://www.seas.harvard.edu/courses/cs181/extension/ Seems these videos are also great.
- tryitnow 15y ago
  This is a great tip. Actually, I was kind of hoping that Ng's course would be focused more on implementation and less on the why, not that the theory is not important, it's just that I have found a lot of other great places on the web to get the theory for free (like the lectures you mentioned).
- hvs 15y ago
  Really? I found descriptions of Linear and Logistical Regression, as well as the descriptions of Support Vector Machines to both explain very well why they work. The Neural Networks description could have been a bit more thorough, but I still understand them much better now than I did before.
brown9-2 15y ago
Personally I find that Professor Ng manages to instill a lot of energy into the ml-class.org lecture videos.
romaniv 15y ago
I partially agree. Complete live sessions are easier to watch when the professor is good and prepared. At the same time, Stanford's format had definite advantages in that it's natively interactive and indexed. If I want to review a concept, I can simply click a link to the appropriate part of the lecture. They also have better sound and image quality.
alphamale3000 15y ago
The ML class is good when watched at 1.5x.
pnmahoney 15y ago
I think the rationale is that - at least as Prof Ng articulated in another ML course he taught this quarter - videos following a lecturer as he teaches on stage are actually _less effective_ than videos which just follow slides w/ audio narration. Another researched case was video lectures with the teacher's face in the corner vs. video lectures with only narration. In which they found that student's information retention was even better without _any_ on-screen presence at all. (Surprising, I know . . . I wish I had a citation, but I'm really just coming in on defense of the department's pedagogical choices here.)

dlo 15y ago

Here are the classroom lectures for ML. http://classx.stanford.edu/ClassX/system/users/web/pg/view_subject.php?subject=CS229_FALL_2011_2012&cxm=1 http://classx.stanford.edu/ClassX/system/users/web/pg/view_s...

dlo 15y ago
Also, the classroom lectures for the upcoming algorithms course are already up. http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=IntroToAlgorithms http://openclassroom.stanford.edu/MainFolder/CoursePage.php?...
sravfeyn 15y ago
Thank you !Is there the original AI class too?
NnamdiJr 15y ago
Thanks a lot for the link. Good way to review and compare with online class.

ot 15y ago

I didn't like Ng's course on ML too much, it is very good if you just want to implement the algorithms, but it gives no insight on why they work. I enjoyed far more Tom Mitchell's lectures, they gave me a much better understanding of the algorithms described: http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml http://www.cs.cmu.edu/~tom/10701_sp11/lectures.shtml There are some comments on HN about it http://news.ycombinator.com/item?id=3199718 http://news.ycombinator.com/item?id=3199718

sravfeyn 15y ago
great! Thanks. I am actually already following ML from Harvard. http://www.seas.harvard.edu/courses/cs181/extension/ http://www.seas.harvard.edu/courses/cs181/extension/ Seems these videos are also great.
tryitnow 15y ago
This is a great tip. Actually, I was kind of hoping that Ng's course would be focused more on implementation and less on the why, not that the theory is not important, it's just that I have found a lot of other great places on the web to get the theory for free (like the lectures you mentioned).
hvs 15y ago
Really? I found descriptions of Linear and Logistical Regression, as well as the descriptions of Support Vector Machines to both explain very well why they work. The Neural Networks description could have been a bit more thorough, but I still understand them much better now than I did before.

brown9-2 15y ago

Personally I find that Professor Ng manages to instill a lot of energy into the ml-class.org lecture videos.

romaniv 15y ago

I partially agree. Complete live sessions are easier to watch when the professor is good and prepared. At the same time, Stanford's format had definite advantages in that it's natively interactive and indexed. If I want to review a concept, I can simply click a link to the appropriate part of the lecture. They also have better sound and image quality.

alphamale3000 15y ago

The ML class is good when watched at 1.5x.

pnmahoney 15y ago

I think the rationale is that - at least as Prof Ng articulated in another ML course he taught this quarter - videos following a lecturer as he teaches on stage are actually _less effective_ than videos which just follow slides w/ audio narration. Another researched case was video lectures with the teacher's face in the corner vs. video lectures with only narration. In which they found that student's information retention was even better without _any_ on-screen presence at all. (Surprising, I know . . . I wish I had a citation, but I'm really just coming in on defense of the department's pedagogical choices here.)