ISMIR 2020 Tutorial for Metric Learning in MIR
- Part 1 Foundations and coding practice: https://www.youtube.com/watch?v=MrAQIYPAmTw
- Part 2 Deep metric learning: https://www.youtube.com/watch?v=laAqMTnwJ4k
- Part 2 Coding practice: https://www.youtube.com/watch?v=E3QHx0YGNwI
- Part 3 Variations and modern applications: https://www.youtube.com/watch?v=HnAgs22PP8k
- Part 3 Closing remarks: https://www.youtube.com/watch?v=DGCAbkt0LE8
The easiest way to follow along with the coding session of the tutorial is to use Google Colab's notebook server. This will require a Google account, but you will not need to install any software on your own machine.
For the first coding demo, follow this link: http://bit.ly/ml4mir-demo-1
For the second coding demo, follow this link: http://bit.ly/ml4mir-demo-2
To use the code, you will need to click the "Connect" button:
After clicking this button and waiting a few seconds, you should have an active notebook instance. You may observe a warning message because the notebook was developed by us (and not Google) -- that's normal. As long as you trust us to write reasonable code, feel free to accept the warning and continue. ๐
You can then work through the notebook by executing each cell with the "play" button or by hitting Shift+Enter
.
If you'd prefer to run the code on your own machine, take the following steps.
- Clone this repository.
- Install miniconda.
- Create a conda environment from the environment specification provided by
metriclearningmir.yml
in this repository. This is done by executing the following command:
conda env create -f metriclearningmir.yml
- Activate the environment:
conda activate metriclearningmir
- You should now be able to run the
Metric Learning Demo.ipynb
orDeep Metric Learning Demo.ipynb
notebook in Jupyter:
jupyter notebook "Metric Learning Demo.ipynb"
or
jupyter notebook "Deep Metric Learning Demo.ipynb"
You may be prompted to change the environment for the notebook when it loads: if so, select metriclearningmir
and you should be all set.
If you prefer to not use conda environments, and already have a working Python (3.6+) installation, you can instead perform the following steps:
- Clone this repository.
- Run the command
pip install -r requirements.txt
(from inside the repository directory).
You can then run
jupyter notebook "Metric Learning Demo.ipynb"
or
jupyter notebook "Deep Metric Learning Demo.ipynb"
just as in the directions above for conda
.
Happy hacking!
You can find references related to this tutorial at the link above.