for computer vision this covers understanding convolutional neural networks (convnetsusing data augmentation to mitigate overfitting using pretrained convnet to do feature extraction fine-tuning pretrained convnet visualizing what convnets learn and how they make classification decisions this introduces convolutional neural networksalso known as convnetsa type of deep-learning model almost universally used in computer vision applications you'll learn to apply convnets to image-classification problems--in particular those involving small training datasetswhich are the most common use case if you aren' large tech company licensed to