Hands-On Meta Learning with Python

Task generation using CACTUs

Let's say we've a dataset set containing samples without labels: . Now we need to create labels for our dataset. How can we do that? First, we learn the embeddings of each of the data points in our dataset using some embedding function. The embedding function can be any feature extractor. Say our input is an image, then we can use CNN as our embedding function for extracting an image feature vector.

After generating the embeddings for each of the data points, how can we find the labels for them? A naive and simple ...