github Not archived

saguiitay/CardinalityEstimation

HyperLogLog-based set cardinality estimation library

2 awesome lists

Quick read

Stars
100
Forks
29
Open issues
4
Commits
132

Activity and growth

Latest capture 2026-11-07 10:54

Stars · last 7 days
0 0.0%
Commits · last 7 days
0 0.0%
Stars since tracking
0
Stored snapshots
1

Compare the starting count and capture dates, not just the percentage. How to read GitHub star growth. Missing history is not zero growth.

Metadata

Language
C#
License
NOASSERTION
Default branch
master
Created
2015-02-02
First commit
2015-02-02
Last pushed
2026-11-06
GitHub updated
2026-11-06
Last synced
2026-11-07 10:54
Stack scanned
2026-11-07 10:54
Archived
No

Archive status reflects the last catalog sync, not a maintenance assessment. Check recent releases, issue responses, and fit for your project with the repository shortlisting checklist.

AI development signals

1 path

Agent instructions and tool configuration found in this repository.

GitHub Copilot

View paths

Explore indexed repositories with these instruction or planning files. File detection is not a quality, compatibility, or safety assessment; check the actual instructions upstream.

AGENTS.md, CLAUDE.md, and GEMINI.md searches also match nested paths. Other file searches require the exact repository-root path. To require several files, select them together in the search filters.

Growth history

Tracked growth

1 observed capture since 2026-11-07. Observed captures are shown by default.

Stars from first capture 0

Chart data

Observed captures only

Time horizon

All tracked data

Custom date range

Stars history

Observed snapshots

Commits history

Observed snapshots

Similar repositories

Nearest indexed repositories by embedding similarity.

l33tdawg/sage

(S)AGE - (Sovereign) Agent Governed Experience

253 stars
Go 2 awesome lists

Leonxlnx/unlazy

Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.

3,988 stars
JavaScript 1 awesome list

unslothai/hyperlearn

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

2,530 stars
Jupyter Notebook 1 awesome list

christopherkarani/Espresso

Run transformers directly on Apple's Neural Engine in Swift bypass coreml entirely

173 stars
Swift 1 awesome list

TheoLeeCJ/SemIf-OpenJev

Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.

4,939 stars
Python 1 awesome list