Mlj.jl
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Jina | 17,845 |  | 2 | 2 days ago | 2,019 | July 06, 2022 | 38 | apache-2.0 | Python | |
| 🔮 Build multimodal AI services via cloud native technologies · Neural Search · Generative AI · Cloud Native | ||||||||||
| Kubeflow | 12,390 | 2 | 15 hours ago | 112 | April 13, 2021 | 397 | apache-2.0 | TypeScript | ||
| Machine Learning Toolkit for Kubernetes | ||||||||||
| Tpot | 8,989 |  | 40 | 18 | a day ago | 60 | January 06, 2021 | 284 | lgpl-3.0 | Python |
| A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. | ||||||||||
| Kedro | 8,199 |  | 8 | 32 | a day ago | 35 | May 09, 2022 | 280 | apache-2.0 | Python |
| A Python framework for creating reproducible, maintainable and modular data science code. | ||||||||||
| Stanza | 6,543 |  | 2 | 68 | a day ago | 17 | April 23, 2022 | 73 | other | Python |
| Official Stanford NLP Python Library for Many Human Languages | ||||||||||
| Augmentor | 4,849 |  | 21 | 8 | 2 months ago | 22 | April 27, 2022 | 132 | mit | Python |
| Image augmentation library in Python for machine learning. | ||||||||||
| Clearml | 4,229 |  | 8 | a day ago | 93 | July 04, 2022 | 307 | apache-2.0 | Python | |
| ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management | ||||||||||
| Deeplearningproject | 4,043 | 3 years ago | 3 | mit | HTML | |||||
| An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. | ||||||||||
| Orchest | 3,773 | 5 days ago | 14 | April 06, 2022 | 124 | agpl-3.0 | Python | |||
| Build data pipelines, the easy way 🛠️ | ||||||||||
| Mage Ai | 3,691 | a day ago | 9 | June 27, 2022 | 54 | apache-2.0 | Python | |||
| 🧙 The modern replacement for Airflow. Build, run, and manage data pipelines for integrating and transforming data. | ||||||||||
A Machine Learning Framework for Julia
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 160 machine learning models written in Julia and other languages.
New to MLJ? Start here.
Integrating an existing machine learning model into the MLJ framework? Start here.
Wanting to contribute? Start here.
PhD and Postdoc opportunies See here.
MLJ was initially created as a Tools, Practices and Systems project at the Alan Turing Institute in 2019. Current funding is provided by a New Zealand Strategic Science Investment Fund awarded to the University of Auckland.
MLJ has been developed with the support of the following organizations:
The MLJ Universe
The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.
Dependency chart for MLJ repositories. Repositories with dashed connections do not currently exist but are planned/proposed.
Contributing • Code Organization • Road Map
Contributors
Core design: A. Blaom, F. Kiraly, S. Vollmer
Lead contributor: A. Blaom
Active maintainers: A. Blaom, S. Okon, T. Lienart, D. Aluthge
