Skip to content

This is the code for "How to Generate Music - Intro to Deep Learning #9' by Siraj Raval on YouTube

License

Notifications You must be signed in to change notification settings

skabbit/How-to-Generate-Music-Demo

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

How-to-Generate-Music-Demo

This is the code for "How to Generate Music - Intro to Deep Learning #9' by Siraj Raval on YouTube

##Overview

This is the code for this video on Youtube by Siraj Raval as part of the the Udacity Deep Learning Nanodegree. It uses Keras & Theano, two deep learning libraries, to generate jazz music. Specifically, it builds a two-layer LSTM, learning from the given MIDI file.

##Dependencies

##Usage

Run on CPU with command:

python generator.py [# of epochs]

Run on GPU with command:

THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python generator.py [# of epochs]

Note: running Keras/Theano on GPU is formally supported for only NVIDIA cards (CUDA backend).

Note: preprocess.py must be modified to work with other MIDI files (the relevant "melody" MIDI part needs to be selected).

#Coding Challenge - Due Date is Thursday, March 16th 2017 at 12 PM PST

The challenge is to generate your own MIDI file! This code trains off of a single MIDI file and the preprocess.py file manually selects the relevant melody part. Modify it so that it selects the melody from your own MIDI file. Bonus points if you train it on not one, but multiple MIDI files. Through training and testing this code, you'll witness just how powerful LSTM networks are and further understand the generative process. Good luck!

##Credits

The credits for this code go to Ji Sung Kim. I've merely created a wrapper to get people started.

About

This is the code for "How to Generate Music - Intro to Deep Learning #9' by Siraj Raval on YouTube

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%