This Jupyter notebook contains a script that uses convolutional neural networks (CNNs) to classify images of cats and dogs. The script uses the Keras library to create a CNN model that is trained on a dataset of images of cats and dogs, and then evaluated on a separate test set. The trained model can then be used to classify new images of cats and dogs.

After training and testing my CNN model on a dataset of cat and dog images, I searched for random cat and dog pictures on Google to evaluate its accuracy. The model was able to classify these images with 88% accuracy. However,the accuracy of the model may vary depending on the quality and diversity of the training data and the complexity of the images being classified. Nonetheless, these results demonstrate that the model is capable of distinguishing between images of cats and dogs with a high degree of accuracy.