Alan turing institute MLJ jl by alan-turing-institute
A Julia machine learning framework
About Alan turing institute MLJ jl
From the project's README at github.com/alan-turing-institute/MLJ.jl. Lightly cleaned for readability; for the full source see the upstream repo.
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing and comparing over 200 machine learning models written in Julia and other languages.
The MLJ.jl package is an umbrella package for components distributed in a number of other packages.
Health score breakdown
6-dimension composite. See methodology for formula and weights.
Adoption signals
Real-world usage data, pulled from each registry. The bigger the numbers, the more battle-tested the project.
| Signal | Value | Source |
|---|---|---|
| GitHub stars | 1.9k | github.com/alan-turing-institute/MLJ.jl |
| GitHub forks | 159 | github.com/alan-turing-institute/MLJ.jl |
Release & maintenance
Is this project actively maintained, or about to die? Check the recency of last commit and last release.
| Project age | 7.8 years | since Aug 2018 |
| Last commit | 3 days ago | May 3, 2026 |
| Releases shipped | 89 | last: 24 days ago |
Self-hosting cost across providers
Detected requirements: 4GB RAM, 40GB disk minimum. Cheapest plan per provider that meets the requirement.
| Provider | Plan | Specs | Monthly | |
|---|---|---|---|---|
| hetzner | CAX11 | 2c · 4GB · 40GB | $4.13 USD | Deploy → |
| vultr | VC2 | 1c · 1GB · 25GB | $5 USD | Deploy → |
| linode | Nanode 1GB | 1c · 1GB · 25GB | $5.12 USD | Deploy → |
| digitalocean | Basic Regular 1GB | 1c · 1GB · 25GB | $6 USD | Deploy → |
Ready to self-host Alan turing institute MLJ jl?
Spin up a hetzner CAX11 (4GB RAM, 40GB disk) for $4.13/mo and follow the project's official install docs.
Data last refreshed May 7, 2026.
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