detection of human emotions
To detect seven human emotions
1.Angry
2.Disgust
3.Fear
4.Happy
5.Sad
6.Surprise
7.Neutral
Kaggle dataset was used here
Training accuracy : 66 percent
Testing accuracy : 62 percent
confusion matrix for the test set containing nearly 7k examples
learning curve 
After 40 epochs the model was starting to overfit with very minute increase in test accuracy so i used early stopping and training and testing accuracy reported here is uptill here. Dropout is used to reduce the overfitting for the model. However an accuracy of ~63-64 percent can be achieved if the model is trained further.
I am open to pull requests and suggestions for improvement of results