Classifying Pictures of Cats and Dogs Using CNNs
The goal here is to create a binary classifier capable of identifying and distinguishing between images of cats and dogs. To achieve this, I will design a convolutional neural network (CNN) using TensorFlow, which is a widely-used open-source framework for machine learning applications. CNNs are advanced deep learning models well-suited for image classification challenges. They include multiple processing layers that apply convolutions and pooling operations to input images, effectively extracting salient features necessary for accurate classification.
I will employ a specific dataset composed of cat and dog images, which has been pre-divided into training, validation, and testing subsets. These subsets are instrumental in both the training phase and the subsequent performance evaluation of the model.