Add data science demos to landing page#2067
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All the demos for this PR have been deployed at https://huggingface.co/spaces/gradio-pr-deploys/pr-2067-all-demos |
| <div class="demo-tab hover:text-gray-800 cursor-pointer px-3 py-1" | ||
| demo="4" | ||
| onclick="load_demo(4)"> | ||
| Time Series Forecasting With Prophet |
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Thoughts on shortening the titles so that they fit better and roughly match the length of the titles of the first 3 demos?
| Time Series Forecasting With Prophet | |
| Time Series Forecasting |
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Sure thing! I was just trying to use eye catching terms lol
| <div class="demo-tab hover:text-gray-800 cursor-pointer px-3 py-1" | ||
| demo="5" | ||
| onclick="load_demo(5)"> | ||
| XGBoost Classification with Explainability |
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| XGBoost Classification with Explainability | |
| XGBoost Classification |
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Looks great @freddyaboulton! Suggest shortening the titles so that they all fit in one line. Also, it seems we are missing code skeletons for the last 2 demos? For the sake of consistency, I think it would be good to include the skeletons. |
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@abidlabs Good point re the code skeleton! I deliberately left them out since they are blocks demos and would need more code than the other demos on the landing page. I thought it would be distracting. If we want to include the code skeleton for blocks, what's the right amount? How about the following? with gr.Blocks() as demo:
# your forecasting demo here
demo.launch() |
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I see, that's a good point. I think that's one option, although the code snippet doesn't really add much. What about leaving out the code snippet then but adding some text that says, "see full code here" and then linking to https://huggingface.co/spaces/gradio/timeseries-forecasting-with-prophet/tree/main? Is it possible to do that in a way that doesn't distract from the demo? |
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Oh nvm you already do that in the demos! Haha that's cool. I'll make some suggestions about the Spaces via PRs on the demos themselves but this LGTM :) |
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Description
Fixes #2048
Added two demos:
Forecasting, Prophet, Tabular datasets, and Prediction Explainability are all concepts that have come up in our conversations with data scientists (both internal and external) and these demos cover those concepts.
My hope is that putting them in the front page will catch the eyes of prospective data science users. The xgboost example is a sneak peek of what we want to be able to automate for skops models.
Checklist: