convolutional neural networks let' make predictions on the validation dataset and visualize the confusion matrix (see listing - listing - making predictions #make predictions on validation dataset actualpredicted make_predictions(val_loaderactual,predicted np array(actualreshape(- , ,np array(predictedreshape(- , print("validation accuracy-",round(accuracy_score(actualpredicted), )* print("\ confusion matrix\ ",confusion_matrix(actual,predicted)output[implementing larger cnn in pytorch sothat was our first sample cnn given the small datasetwe could comfortably train our network on our personal computer (commodity hardwareand still achieve favorable results let' explore similar example but with more complicated images good example in this category would be the cats and dogs dataset hereour objective is to classify the dataset as cats or dogs based on given image