sjwhitworth/golearn
Machine Learning for Go observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4633
- days_rel: n/a
- days_push: 961
- n_releases_24m: 0
Adoption not part of the score
9439 stars · 1164 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
GoLearn is a 'batteries included' machine learning library for Go with a scikit-learn-style Fit/Predict interface. It provides data loading via Instances, train/test splitting, cross validation, and estimators like KNN with evaluation metrics.
Use cases
- train a classifier in go
- load csv datasets for machine learning
- knn classification in golang
- compute confusion matrix and precision recall
- split data into train and test sets
- scikit-learn style ml in go
When to choose
- you need simple, batteries-included ML in a Go codebase
- you want a familiar Fit/Predict API like scikit-learn
- you need basic classification with evaluation metrics
When to avoid
- you need deep learning or GPU acceleration
- you need the breadth of estimators available in Python's scikit-learn
- you need a very actively developed library with frequent releases
Facets
library · maturity maintenance
machine-learning data-science serialization machine-learning data-science go cross-platform scikit-learn-style knn classification csv cross-validation
1 source
- readme: https://github.com/sjwhitworth/golearn · fetched 2026-08-28 · d855e458ae61
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| sjwhitworth/golearn | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="sjwhitworth/golearn")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem