Cats and Dogs Prediction Classifier This GitHub repository hosts a sophisticated image classifier designed to discern between cats and dogs through Convolutional Neural Networks (CNNs). The model showcases exceptional performance with a training accuracy of 98% and sustains a high testing accuracy of 97%. Image preprocessing is accomplished using OpenCV, while Matplotlib is employed to visualize the processed images. TensorFlow, a powerful deep learning library, is utilized to implement the CNN architecture. The project incorporates essential metrics such as accuracy to assess model performance, and the Adam optimizer is chosen for efficient training.