Yushi Wang, Jie Fu, Yumeng Yin
This competition was mainly done by Yushi Wang
.
Due to the configuration problems with neon
, we haven't had enough time to tune the hyperparameters. Our solution is first do some filtering in the frequency-domain, and then train a CNN in the space-domain.
We put code, experimental procedure, documents, discussion and resources here. As for project management, we use Trello. For light chat, we stick with Gitter.
- SKlearn
- Neon, https://github.com/NervanaSystems/neon
- Theano, http://deeplearning.net/software/theano/
- Keras
- RoBO
- Hyperopt, https://github.com/hyperopt/hyperopt
- https://www.kaggle.com/anlthms/grasp-and-lift-eeg-detection/convnet-0-89 Sample code with
Neon
- Do filtering in the frequency-domain
- Transform back to space-domain, and train deep neural networks
- Tune hyperparameters using
RoBO
orhyperopt
When submitting, we create our own folders, such as fj_submit
- rnn_baseline
.
Dense documentation is desired. So put all the thoughts and related stuff in markdown
files associated with the code and data.