#Contains a two layer ANN and a two convo-pooling layered CNN
#to get the various features of costumers of a hypothetical bank, and uses it to predict whether the costumer leaves or stays
#can be applied to equiavalent classification problem
#the classic CNN that classifies the image as a DOG or a CAT
*The CNN model was trained on 8000 images(equally for cats and dogs), and 2000 test images were tested. *
Also, the data was neatly categorized into training set and test set, with the dogs and the cats seperated into folders
The CNN was found to be overfit for this classification task, so only one convo-pooling layer did a fine job of generalizing.
//updated