Cats vs. Dogs Image Classifier using Convolutional Neural Networks (CNN)
This repository contains an image classification model built using Convolutional Neural Networks (CNN) to distinguish between images of cats and dogs. The model is trained on the popular "Dogs vs. Cats" dataset sourced from Kaggle, consisting of thousands of labeled images of cats and dogs.
Dataset
The dataset used for training and evaluation can be found on Kaggle: Dogs vs. Cats Dataset. It includes a vast collection of images, with each image labeled as either a cat or a dog. The dataset is well-suited for training machine learning models to differentiate between these two common pets.
Model Architecture
The image classification model utilizes a CNN architecture, a powerful deep learning technique widely used in computer vision tasks. The architecture comprises multiple layers of convolutional and pooling operations followed by fully connected layers to learn intricate patterns and features from the input images.