On the recordRead 12 Oct 202627 facts
MLJ.jl
On the record
- Acceleration
- Supported workflows can use CPU threading or multiprocessing; serial CPU processing is the default.juliaai.github.io · read 12 Oct 2026
- Additional packages
- Users generally need to add model-providing packages to access model-specific code, and MLJ's interactive load command can prompt for a provider.juliaai.github.io · read 12 Oct 2026
- Audience
- The project welcomes contributors who can demonstrate prior experience in Julia and machine learning.juliaml.ai · read 11 Oct 2026
- Bayesian analysis
- Yesgithub.com · read 23 Sep 2026
- Composition
- MLJ supports pipelines, stacks, and learning networks for composing models.juliaai.github.io · read 12 Oct 2026
- Core functions
- MLJ provides a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing machine learning models.juliaai.github.io · read 12 Oct 2026
- Data import formats
- CSV (CSV.jl), DataFrames/Tables.jl tables, RDatasets, OpenMLgithub.com · read 23 Sep 2026
- Data support
- MLJ works with data supported by the Tables.jl interface when Tables.istable(X) is true.juliaai.github.io · read 12 Oct 2026
- Evaluation and tuning
- MLJ provides syntax to tune and evaluate composite models and supports probabilistic predictions.juliaai.github.io · read 12 Oct 2026
- Installation
- MLJ is installed with Julia's package manager using Pkg.add("MLJ").juliaai.github.io · read 12 Oct 2026
- Integrations
- MLJ's ecosystem includes OpenML.jl integration for the OpenML data science exchange platform.juliaml.ai · read 12 Oct 2026
- Learning networks
- Learning networks can train multiple models together and can be exported as standalone model types.juliaml.ai · read 11 Oct 2026
- License
- MLJ is open source and released under the MIT license.juliaml.ai · read 12 Oct 2026
- Model coverage
- The documentation says MLJ supports over 180 machine learning models written in Julia and other languages, including many scikit-learn models.juliaai.github.io · read 12 Oct 2026
- Model registry
- Its model registry contains metadata for models that users can search and load on demand.juliaml.ai · read 11 Oct 2026
- Model support
- The MLJ ecosystem includes support for neural network models built with Flux.jl.juliaml.ai · read 11 Oct 2026
- Pipelines
- Pipelines can combine model components, and their parameters can be tuned together.juliaml.ai · read 11 Oct 2026
- Project history
- The MLJ project began at the Alan Turing Institute in 2019 as a Tools, Practices and Systems project.juliaml.ai · read 12 Oct 2026
