  Artificial Neural Networks, an essential part of Deep Learning, are derived
from the structure and functionality of the human brain. It has a broad range
of applications ranging from medical analysis to automated driving. Over the
past few years, deep learning techniques have improved drastically - models can
now be customized to a much greater extent by varying the network architecture,
network parameters, among others. We have varied parameters like learning rate,
filter size, the number of hidden layers, stride size and the activation
function among others to analyze the performance of the model and thus produce
a model with the highest performance. The model classifies images into 3
categories, namely, cars, faces and aeroplanes.
