Few-Shot Learning Explained for Beginners

Few-Shot Learning is a method where computers learn to solve new tasks with only very few examples.

Imagine you are learning a new sport and have only practiced a few times – yet you can already understand and apply quite a bit of it.

Similarly, the computer tries to learn quickly from few data points without needing many training examples.

This is especially important when only little data is available or collecting data is expensive and time-consuming.

This way, computers can respond more flexibly and quickly to new situations.