Cats vs Dogs Classification with Convolutional Neural Networks

This project aims to build a binary classifier to distinguish between the images of cats and dogs. For this purpose, we will build a convolutional neural network (CNN) using TensorFlow, a popular open-source software library for machine learning. CNNs are a type of deep learning algorithms that are particularly effective for image classification tasks. They consist several layers that perform convolutions and pooling operations on the input images to extract important features.

We will use a dataset of images containing cats and dogs. This dataset is split into training, validation, and testing sets for training and evaluation purposes.