These are chat archives for FreeCodeCamp/DataScience
discussion on how we can use statistical methods to measure and improve the efficacy of http://freeCodeCamp.com
@alicejiang1 sorry, I haven't heard of any. Are you wanting to generate music based on already available music? It would be interesting for something to generate music an artist has never created but is in the same style.
Someone was able to something tangent with art where you yourself would sketch something and then run the drawing through an algorithm and then it would pop out a drawing that is in the style of one of the famous artists.
I couldn't find the software that does that. However, while trying to look for that, I stumbled upon something even cooler! Someone's been able to take pre-existing art and extend it! Here's the site with famous art pieces extended as if the original artists painted more.
Sorry if this seems off-topic, but I would like to know if the GTX 1060 6GB suffices to replicate some recent things like Wavenet or matching muted videos with sound without spending weeks training the model - I don't want to waste money on a graphics card which is too weak for this purposes.
I've read a very comprehensive guide but I'm still unsure what accuracy I have to expect after several pooling layers. Did someone try Tensorflow implementations of those projects on this GPU (although I know that TF may be slower)? Would be glad to hear some GTX 1060 users.
And the music project sounds like fun, this project seems to do the same. Maybe it's easier to train two models: one for generating sheets of music based on training data (e.g. outputting MIDI files which encode relevant information for synthesis, like DeepJazz which uses MIDI files for training) and another one which synthesizes the sound. This may enable the second model to use music by e.g. Mozart and synthesizing it using modern/rock sounds (like "A Neural Algorithm of Artistic Style" for music, although I think that artistic videos are conceptually more similar to music generation than generating one image) and you may profit from TTS research. Google Brain with Magenta seems to be very interested in that topic, too.
The research of David Cope "Experiments in Musical Intelligence" may be interesting for you, I was stunned when I first heard his creation Emily Howell which is able to analyze structure and repetitions in its training data.
Maybe it's a funny idea to use DQN and Reinforcement Learning techniques, but I wouldn't know what the reward function should look like.
Another spontaneous idea would be to encode the pitch as a number and use n-grams Markov model to create music based on trained music - I'm not sure if this is a good idea or would generate good music, but I've seen it to create poems. Music is normally very structured and this may help to assign appropriate probabilites and imitate that structure of chorus and verse.