# Deep Learning Tutorials

## How to use Deep Lake for Deep Learning Applications

Deep Lake can be used as tool for managing Deep Learning data, including rapidly training models while streaming data, running queries, tracking dataset versions, visualizing datasets, and more.

These tutorials show how to use Deep Lake's low-level API for deep-learning use cases. 

### Deep Learning Tutorials:

{% content-ref url="deep-learning/creating-datasets" %}
[creating-datasets](https://docs-v3.activeloop.ai/v3.6.9/tutorials/deep-learning/creating-datasets)
{% endcontent-ref %}

{% content-ref url="deep-learning/training-models" %}
[training-models](https://docs-v3.activeloop.ai/v3.6.9/tutorials/deep-learning/training-models)
{% endcontent-ref %}

{% content-ref url="deep-learning/updating-datasets" %}
[updating-datasets](https://docs-v3.activeloop.ai/v3.6.9/tutorials/deep-learning/updating-datasets)
{% endcontent-ref %}

{% content-ref url="deep-learning/data-processing-using-parallel-computing" %}
[data-processing-using-parallel-computing](https://docs-v3.activeloop.ai/v3.6.9/tutorials/deep-learning/data-processing-using-parallel-computing)
{% endcontent-ref %}


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# 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://docs-v3.activeloop.ai/v3.6.9/tutorials/deep-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.