title: One-Shot Learning
Humans learn new concepts with very little need for repetition – e.g. a child can generalize the concept
of a “monkey” from a single picture in a book, yet our best deep learning systems need hundreds or
thousands of examples to grasp any object even upto a point of decent accuracy. This motivates the setting we are interested in: “one-shot” learning, which
consists of learning a class from a single (or very few) labelled example.
There are various approaches to One-Shot learning such as similarity functions,
Bayes’ probability theorem, DeepMind has come up with it’s own version of Neural Networks using the One-Shot learning approach!