umap VS squoosh

UMAP GitHub repository: https://github.com/lmcinnes/umap

Uniform Manifold Approximation and Projection (UMAP) is a well-known dimensionality reduction method along with t-SNE.

A number of excellent topic modeling libraries exist in Python today. BERTopic and Top2Vec are two of the most popular. Both use sentence-transformers to encode data into vectors, UMAP for dimensionality reduction and HDBSCAN to cluster nodes.

As with anything, it depends on the problem. But T-SNE and UMAP are often good.

UMAP distances.py: umap/distances.py at master · lmcinnes/umap (github.com)

I used for this project Flask and OpenAI CLIP. For the vector search I used approximate nearest neighbors provided by spotify/annoy. I used Flask-SQLAlchemy with GeoAlchemy2 to query GPS coordinates. The embedding was done using UMAP.

side note: instead of t-SNE consider UMAP - provides better results (and it's much faster) https://github.com/lmcinnes/umap

Sounds like a job for UMAP https://github.com/lmcinnes/umap ?

I am a fairly experienced python developer/researcher (about 10 years), and have found a bug that breaks all of my intuitions. I am messing with the [UMAP](https://github.com/lmcinnes/umap) repository and trying to add the option to disable some additional features. I've stripped everything from it but have a [quick test that will run my UMAP version and compare the outputs with what the original gave](https://github.com/Andrew-Draganov/probabilistic_dim_reduction/blob/master/umap/nndescent_umap_test.py). Managing my random seeds, same inputs, all that.

I'm currently reading through a project on github, https://github.com/lmcinnes/umap, and in `umap/umap_.py` at line 2287, they have this:

Here's another handy tool that I use: https://squoosh.app/

Squoosh: A webpage that allows you to quickly optimize images for your blog.

One of the most complete image compressor out there, squoosh.app by Google, uses web assembly for decoding/encoding images and it works pretty well.

First off you want to shrink your images. Every mb your page is the more it will hurt your score. I use https://squoosh.app/

https://squoosh.app/

Having a quick look at squoosh, it uses lossy compression of webp by default.

Size images appropriately (https://squoosh.app/ can be used for this). Ideally, the size of the image should be kept below 100 KB.

if your images a large file size, remove them from the page, reduce file size, and place new reduced file size images in their place - publish the site to bring the new pics live - clear your cache - go the page and test it (good tool to reduce image file size is Google Squoosh - https://squoosh.app/ )

I'm just exporting normally from Figma, but then using squoosh.app (browser based) to adjust quality/compression and even for making sure png files are optimized for prod.

Hey I see your friend made a clan, but this guy found a workaround here if you still need it. I just used https://squoosh.app/ to basically save a new copy of the image and that worked