Image processing is a very popular topic in machine learning. The idea is pretty self-explanatory: creating models that can analyze images and make inferences on top of them. By inference, you can understand this as detecting objects in an image, classifying images, and so on.
AWS offers a set of built-in algorithms we can use to train image processing models. In the next few sections, we will have a look at those algorithms.
Image classification algorithm
As the name suggests, the image classification algorithm is used to classify images using supervised learning. In other words, it needs a label within each image. It supports multi-label classification.
The way it operates is simple: during training, it receives an image and its associated labels. During inference, it receives an image and returns all the predicted labels. The image classification algorithm uses a CNN (ResNet) for training. It can either train the model from scratch or take advantage...