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+# dl-eeg-playground
+You have found the Deep Learning EEG Playground, put together by the Montreal Hacknight. 
+
+The repo is a bit messy, but what you should find in here:
+- examples on how to usual stuff with colab
+- a pyRiemann comparative example
+- brain-decode based experimentations:
+    - tutorial from their website
+    - x86 execution
+    - colab based code
+    - sklearn wrapper
+    
+We are currently working toward integrating braindecode into MOABB, feel free to join us every other Fridays @ District 3 Innovation Center
+
+
+# SETUP
+
+- We assume you are using Anaconda, python 3.5
+
+- Install Brain Decode: https://github.com/robintibor/braindecode
+  - If you are on Windows, [You can install PyTorch using these instructions. You only need to go up to step 4.A.](https://www.superdatascience.com/pytorch/) 
+- Go through the TrialWise Tutorial: https://robintibor.github.io/braindecode/notebooks/TrialWise_Decoding.html to make sure everything is setup properly
+- Download this dataset : Two class motor imagery (002-2014) at http://bnci-horizon-2020.eu/database/data-sets
+- put everything in an new folder (here)/BBCIData/
+
+The remaining of the project is described in our jupyter notebook(s)
+1 - Two-Classes Classification (BNCI)
+
+# SETUP (Google Colab)
+
+1. Download `2 - Two-Classes Classification (BNCI) Colab.ipynb` and upload it on your Google Drive.
+1. Open [Google Colab](https://colab.research.google.com)
+1. Instructions for dataset download and python library installation are described in the Jupyter notebook.
+
+## Resources
+For more papers on DL applications on EEG, you could refer to this [repo](https://github.com/arnaghosh/DL-neuro_Papers). Feel free to contribute.