1.2 KiB
1.2 KiB
| title |
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| One-Shot Learning |
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!