It is a binary classifier built using an artificial neural network. This is being used to classify images of a dataset into two classes which are “cat” or “not cat”. The neural network is made from scratch with atomic units as neuron which contains the activation functions. The classifier is made in Python language with efficient use of concepts of object-oriented programming.
- Performance on training data
- Performance on testing data
Accuracy : 80%
