# Building An Intent Recognition Classifier

:::callout{intent="note" title="This is an interactive tutorial!"}
To run this tutorial, click on **Examples** and select one of the options.
:::

Chatbots are designed to understand and respond to human language. They need to be able to understand the text they hear and understand the context of the conversation. They also need to be able to respond to people’s questions and comments in a meaningful way. To accomplish this, chatbots must be able to recognize specific intents that people express in conversation.

Here is an example of classifying the intent of customer inquiries on an eCommerce website into `Shipping and handling policy`, `Start return or exchange`, or `Track order`.

## Set up

Install the SDK.

```
$ pip install cohere
```

Set up the Cohere client.

```
import cohere  
co = cohere.Client(api_key)
```

## Add examples

These are the training examples we give the model to show the classes we want it to classify. Each example contains the text itself and the corresponding label, or class. The minimum number of examples required is five per class.

## Related pages

- [Changelog](../changelog.md)
- [Cohere](../index.md)
- [Cohere API](./cohere-api-index.md)
- [Cohere Labs](./cohere-labs-index.md)
- [Cohere Platform](./cohere-platform-index.md)
- [Cookbooks](./cookbooks-index.md)
- [Deployment Options](./deployment-options-index.md)
- [Embeddings (Vectors, Search, Retrieval)](./embeddings-vectors-search-retrieval-index.md)
- [Get Started](./get-started-index.md)
- [Going to Production](./going-to-production-index.md)

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