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:
- Metrics and Graphics standardization with Scikit Plot
- Dimensionality reduction with UMap
- Interpretation of clusters with Skope Rules
- For times when the dataset keeps growing and your resources stay the same you call Faiss
- Demo-ing a webpage (so to speak...you'll see!) with Streamlit directly from Deepnote learned from here
And the 3 bonus are:
- Draw data (the cover image origin!)
- A Dockerfile to smoothly run Faiss
- 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