# N-Shot Learning

### N-SHOT LEARNING

1. [Zero shot, one shot, few shot](https://blog.floydhub.com/n-shot-learning/) (siamese is one shot)

### ZERO SHOT LEARNING

1. [Instead of using class labels](https://www.youtube.com/watch?v=jBnCcr-3bXc), we use some kind of vector representation for the classes, taken from a co-occurrence-after-svd or word2vec. - quite clever. This enables us to figure out if a new unseen class is near one of the known supervised classes. KNN can be used or some other distance-based classifier. Can we use word2vec for similarity measurements of new classes?\
   ![](https://lh3.googleusercontent.com/Rim9_QVRRSj7eJTYeCcs1FfXzf-k7Qp2Wdmgcd1H-N_ZZ6-krl1O3pH8GLkZMAVk2eQ5Ye_Os2nUMqqsKzq92iP2rtlt1lix_KnsMQsSrpMDPYcqI02TU0RrcZZMBmqfiLQj7xeN)\
   Image by [Dr. Timothy Hospedales, Yandex](https://www.youtube.com/watch?v=jBnCcr-3bXc)

   \
   for classification, we can use nearest neighbour or manifold-based labeling propagation.\
   ![](https://lh4.googleusercontent.com/nwZTsm4rfemR9-hNsyVpn1sFc4jJ9b2RAf_gZKds51ki81crI9_C6L5xI5M1F7OMK6a2Et7vS4JKWwtFMODKj_RfQ6jTmCtrSPfQb4jMoZrZ5ZEoIm4uxublmBTgkJLkSvsMqYYF)\
   Image by [Dr. Timothy Hospedales, Yandex](https://www.youtube.com/watch?v=jBnCcr-3bXc)\
   Multiple category vectors? Multilabel zero-shot also in the video
2. [with siamese networks](https://towardsdatascience.com/zero-shot-intent-classification-with-siamese-networks-35900471c7fd)

#### GPT3 is ZERO, ONE, FEW

1. [Prompt Engineering Tips & Tricks](https://blog.andrewcantino.com/blog/2021/04/21/prompt-engineering-tips-and-tricks/)
2. [Open GPT3 prompt engineering](https://medium.com/swlh/openai-gpt-3-and-prompt-engineering-dcdc2c5fcd29)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://www.mlcompendium.com/types-of-machine-learning/n-shot-learning.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.