Building interactive demos for examples

### Describe the issue linked to the documentation

This is not an issue but rather a good-to-have feature for documentation and this issue is more of a discussion.

It would be nice to have links to or embedding interactive demos made with Gradio inside documentation. 
I've built two apps that you might see how it looks like:
- Anomaly detection: https://huggingface.co/spaces/scikit-learn/anomaly-detection
- Classification: https://huggingface.co/spaces/scikit-learn/classification

We can have below demo (but more official version 😅) embedded in your documentation.
<img width="1155" alt="Ekran Resmi 2022-11-10 15 11 41" src="https://user-images.githubusercontent.com/53175384/201114005-5fd13d40-990a-412d-abe6-fdd01d0f87d9.png">

The current workflow for users is to download python code or run binder. This reduces amount of work in this workflow too!
If you think embedded demos is a bit overkill what we could do is to create these demos and host them on [Spaces](https://huggingface.co/spaces) and put link to Space instead (like it is with Keras examples or kornia examples, you can see them [here](https://huggingface.co/keras-io) and [here](https://huggingface.co/kornia), they're linked from their tutorials on both [Keras.io/examples](https://keras.io/examples/) and Kornia docs) We will also host the Spaces in better hardware (8 vCPU 32 GiB RAM) to make sure it's always running and all good. ✨ 

You can see how it's implemented in Kornia for rst docs [here](https://raw.githubusercontent.com/kornia/kornia/627ebcaaab1547c362908fc9ad9a68c6316c5993/docs/source/filters.rst). It looks like [this](https://kornia.readthedocs.io/en/latest/filters.html#interactive-demo) inside Kornia docs.

<img width="1353" alt="Ekran Resmi 2022-11-10 15 15 08" src="https://user-images.githubusercontent.com/53175384/201114865-d44b6af5-0b85-44d1-b490-0450d8ea05aa.png">

As for Keras, we just put a redirection link inside docs since their document generation is more layered.  
<img width="1309" alt="Ekran Resmi 2022-11-10 15 09 57" src="https://user-images.githubusercontent.com/53175384/201113694-a4c5b804-dce4-4e72-b23e-bbe449bbc150.png">

We definitely want to reduce the core maintainers' workflow so what would be cool is that we (team at [Gradio](https://gradio.app/) & community)  will be developing the demos and maintaining them through GitHub actions such that they will not break every time there's a breaking change in sklearn (this happens rarely, though 🙂)

Hoping to see how we could collaborate!

COMMENT:
For the scikit-learn examples, some work is needed to integrate JupyterLite into sphinx-gallery, see https://github.com/sphinx-gallery/sphinx-gallery/pull/977 for an attempt by Andreas for example (full disclosure I haven't looked at it in details).

Also there are caveats down the road:
- there are weird low-level bugs in Pyodide e.g. see https://github.com/pyodide/pyodide/issues/3203
- "magical" imports don't work for all the packages that we use in our examples. For example "import plotly" does not work you need to do `import piplite; await piplite.install('plotly')`. I think not that many examples use plotly so maybe not a crucial issue for now. For the general case, you would need to generate a slightly different notebook if you are inside JupyterLite compared to when you are in a normal notebook (e.g. Binder), not sure how that would be doable ... the alternative would be to use [jupyterlite-xeus-python-kernel](https://github.com/jupyterlite/xeus-python-kernel) that could in principle install all the dependencies from emscripten-forge. In my small tests with jupyterlite-xeus-python-kernel, as soon as you have numpy, the start-up time of the kernel takes a very long time and as things stand today is not such a nice user experience.

Labels: Documentation, RFC