It seems to me these have been narrated by a professional. The narrator's voice is pleasant and pronunciation clear, but it seems he doesn't really know what he's talking about.
I would prefer the voice of an actual subject matter expert; they would be able to better convey which parts are actually key concepts, and which parts are just intermediary math. Now it feels like everything is equally important, when it's clearly just some intermediary math to get you to the actually interesting part that follows.
I agree that the continuous music is distracting. The quick fix is to fade the music away for the content. It would be fine to leave in for the beginning, end, and transitions.
1) The music and choice of narrator is getting in the way of the (presumably valuable) content.
2) The content itself, regardless of the choice of narrator or whether or not there's music behind it, is not useful.
If it's the latter then why complain about the former?
1. High pitch voice. Either it is modulated or not, the voice informs us that a person we are listening to is low social status, therefore subconsciously we assign lesser significance to anything he says.
2. Infomercial-like intonation. Guy may be professional narrator, and his intonation is like you would find in advertisements where someone tries to sell you something really worthless. So people again subconsciously tend to "categorize" this kind of information as unwanted and are used to filtering it out. The effect is strengthened by the choice of music.
3. The narrator clearly has no understanding (or gives that impression) about the subject he is told to talk about. This is subconsciously felt by people through his intonation and the way to put emphasis on random words, and that also translates to two things: again reminds us of infomercials (meaningless talking to occupy time) and malicious persuasion - he wants me to believe in something he does not believe (actually does not understand).
This all adds up to our brain signaling something is wrong, therefore complaints. There is more to education than content.
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- why the music? should this be information or an awfully mixed guitar rap song with the worst flow ever? i can't stand the use of elevator music in these kind of videos and also regard this kind of video production as an act of disrespect towards music in general.
- why not use more descriptive variable names, e.g. hours and score instead of x and y? the mystification of these kind of things comes partially from generalised abstraction and undescriptive variable names. since you already use a real world example, why not reflect it with the variable names?
- less speed, more pauses in general do good for demystification of such a topic, the typical 10-second-attention-span youtube-edutainment-video-style might not really fit here
- the drawings and the general flow are nice and well done
One suggestion: What if you embedded the ipython notebooks that go along with each video into the page so that people could follow along? Even if it is static html like you see here http://blog.fperez.org/2012/09/blogging-with-ipython-noteboo... and not an actual hosted notebook.
Embedding notebooks is an interesting idea, I'll experiment with implementing it.
It would be cool if there were pointers to recommended videos/courses from other organizations (Stanford, MIT, etcetera) for further learning.
PS: I would have wished my college classes had such relaxing background music :)
[1]: https://www.youtube.com/playlist?list=PLiaHhY2iBX9hdHaRr6b7X...
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I neither have the time nor the brain to do this. Fascinating stuff, though.
Plan B: To avoid boredom, present the material as quickly and densely as possible, with lots of constantly changing detail, with simultaneous visual, audio and even some light background music.
These videos are a bit like "Hitchhiker's Guide to the Galaxy" meets "Khan Academy".
Some people will like them, and some won't. I like them.
Also these lecture notes https://github.com/joanbruna/stat212b
Of course, there are still many open questions. But I don't think that there is any aspect where there is no analysis available yet.
There is certainly no shortage of new tutorials bubbling up on neural nets. One of my favorites - https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearni...
Link to Installation of Anaconda(by Continuum): https://www.continuum.io/downloads
Link to the Git Repo: https://github.com/stephencwelch/Neural-Networks-Demystified
I know a lot of developers like myself that know about traditional NNs, but are not familiar with those two.
I also have an article on RNNs, although it's focused on explaining a special version, called an LSTM: http://colah.github.io/posts/2015-08-Understanding-LSTMs/
If you have experience with functional programming, you might find this a nice way to think about Conv Nets/RNNs/etc: http://colah.github.io/posts/2015-09-NN-Types-FP/
I'm not sure i would be able to just write (or decide) the equation for the neural network. On what criteria can you decide this will work better or not? What are your key to make a decision?
Otherwise, good job.
Does somebody know a source for a nice data analytics/machine learning taxonomy or something (grouped by the class of problems the different methods solve)..?