- Visualisation : We have visualised our dataset in python with the help of matplotlib library. We have represented the data in terms of pie chart and bar graph.
- KNN : We have applied the k -nearest neighbours model on our dataset with k=1 and L1 as the distance metric.
- NN : We have tried neural network on our dataset.
- Basic CNN : We have made use of basic CNN by using less number of Convolution and Pooling layers.
- Complex CNN : We have applied complex CNN by increasing the number of convolutional and pooling layers used in basic cnn.
- Transfer Learning : We have done transfer learning using Resnet,Inception Net and VGG-16
- Comparison : We have compared the above mentioned models with the help of bar graph on the basis of accuracy, precision,recall and F1-score.
We have also made use of data downsampling and data augmentation in our project.