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✨ 5 Best GitHub Repositories to Learn Machine Learning in 2022 for Free 💯
5 projects | reddit.com/r/learnmachinelearning | 14 Oct 2022
4️⃣ Homemade Machine Learning
Introducing the Semantic Graph
5 projects | dev.to | 16 Sep 2022
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.
Introduction to K-Means Clustering
5 projects | news.ycombinator.com | 14 Mar 2022
Working in spatial data science, I rarely find applications where k-means is the best tool. The problem is that it is difficult to know how many clusters you can expect on maps. Is it 5, 500, or 10,000? Here HDBSCAN  shines because it will cluster _and_ select the most suitable number of clusters, to cut the single linkage cluster tree.
[D] Good algorithm for clustering big data (sentences represented as embeddings)?
5 projects | reddit.com/r/MachineLearning | 31 Mar 2021
Maybe use (H)DBScan which I think should work also for huge datasets. I don't think there is a ready to use clustering with unbuild cosine similarily metrics, and you also won't be able to precompute the 100k X 100k dense similarity matrix. The only way to go on this is to L2 normalize your embeddings, then the dot product will be the angular distance as a proxy to the cosine similarily. See also https://github.com/scikit-learn-contrib/hdbscan/issues/69
What are some alternatives?
faiss - A library for efficient similarity search and clustering of dense vectors.
Top2Vec - Top2Vec learns jointly embedded topic, document and word vectors.
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
Milvus - A cloud-native vector database, storage for next generation AI applications
wordle-solver - For educational purposes, a simple script that assists in solving the word game Wordle.
rmi - A learned index structure
PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features
PythonRobotics - Python sample codes for robotics algorithms.
raku-jupyter-kernel - Raku Kernel for Jupyter/IPython notebooks
CFDPython - A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
AlgorithmicTrading - This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.