ImageClassifier

The image classifier for cats and dogs is a deep learning model designed to accurately distinguish between images of cats and dogs. Leveraging a convolutional neural network (CNN) architecture, the model processes pixel data from input images, learning to identify and differentiate the unique features and patterns that characterize each animal. The model is trained on a large dataset of labeled cat and dog images, using a portion of the data for training and another for validation to tune hyperparameters and avoid overfitting. The training process involves multiple epochs where the model iteratively refines its parameters to minimize the prediction error. Once trained, the model's performance is evaluated on a separate test set, ensuring it generalizes well to new, unseen images. The classifier's effectiveness is measured using metrics such as precision, recall, and accuracy, providing an understanding of its performance.