Update: I finished 2nd in the showcase competition of Deepnote, great success! 🤩 https://community.deepnote.com/c/announcements/deepnote-publishing-competition-results

Hey! how are you? I'm publishing this notebook to share some libraries, tips and tricks for clustering problems. I strongly advice, check it on Deepnote by clicking the badge!

I'm skipping all the explanations that you can find in Sklearn, because the idea is share my current tools in a quick way. Even with this point made, everyone with some interest or experience in clustering is welcome to talk or comment 😀

These are the 5 topics:

1. Metrics and Graphics standardization with Scikit Plot
2. Dimensionality reduction with UMap
3. Interpretation of clusters with Skope Rules
4. For times when the dataset keeps growing and your resources stay the same you call Faiss
5. Demo-ing a webpage (so to speak...you'll see!) with Streamlit directly from Deepnote learned from here

And the 3 bonus are:

1. Draw data (the cover image origin!)
2. A Dockerfile to smoothly run Faiss
3. This github repo (this one is a little bit humble and kind of a circular reference 😂)

I publish this in https://deepnote.com/@tomas-bonfiglio/Enhance-your-clustering-projects-T176oVvEQZWXnoZZkusECA