## ToDo
### Report
* write **Kaggle Competition: Diabetic Retinopathy Detection** section in your own words
* include stats of the data set provided in terms of the number of examples per class
* some of the **DL Frameworks** review parts are direct copy/paste - make sure it is all written in your own words.

### Pre-training second layer
* make sure pre-training values are between 0.1 and 0.9 (actually look into existing datasets used for the pretraining and see what min and max values do they use)

train first layer with unsupervised training

* convolve input data with learned filters
* replace inputs with feature maps (1 -> 64)
* create 200k samples of 64x13x13 tensors use them to pre-train second layer filters (2048 -> 512). Should I keep the connection table with me (would not hurt I guess).



## Notes
* Use Photoshop to mark symptom features for supervised learning. Save PSD files, where one layer is the original image and second layer is features marked with different color for each.
* Extracting filenames in labels.csv:
```
    cat trainLabels.csv | grep ",1" | head -n20 | awk -F "," '{print "processed/train/"$1".jpeg"}' | xargs open
```