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 about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization.

Features

  • Model Browser
  • Work with Categorical Data
  • Evaluate Model Performance
  • Compose models
  • Log Workflows
  • Customization and Extension

Project Samples

Project Activity

See All Activity >

Categories

Frameworks

Follow MLJ

MLJ Web Site

Other Useful Business Software
Build Securely on AWS with Proven Frameworks Icon
Build Securely on AWS with Proven Frameworks

Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
Download Now
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of MLJ!

Additional Project Details

Programming Language

Julia

Related Categories

Julia Frameworks

Registered

2023-11-02