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Topics: recommendation

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3 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)

Language: Python
Topic: recommendation
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1.recommenders-team / recommenders

Best Practices on Recommendation Systems

machine-learning
recommender
ranking
deep-learning
python
jupyter-notebook
+11 more

Python MIT22K total3.3K forks

+8 stars

from 21,965 · score 2.20

2.NicolasHug / Surprise

A Python scikit for building and analyzing recommender systems

recommender
systems
recommendation
svd
matrix
factorization
+1 more

Python BSD-3-CLAUSE6.8K total1.1K forks

+3 stars

from 6,821 · score 1.39

3.benfred / implicit

Fast Python Collaborative Filtering for Implicit Feedback Datasets

collaborative-filtering
machine-learning
matrix-factorization
recommender-system
recommendation-system
recommendation

Python MIT3.8K total632 forks

+2 stars

from 3,832 · score 1.10

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before a repository's first Observation. A longer window needs more days of Observations first. A repository younger than the window is not ranked in it.

The filters narrow the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Category holds the repositories that its published rules match; see Categories.

Repositories enter the index from the Seed Dataset or by gaining stars faster than the published admission threshold, whatever their size. Admission is permanent, so an archived repository can still rank.

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