IBM/AutoMLPipeline.jl
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
This package helps machine learning practitioners design and test complex prediction models. It takes raw datasets, processes them through various steps like feature extraction and scaling, and then applies different modeling techniques. The output is a highly optimized and evaluated machine learning model ready for tasks like classification or regression.
371 stars.
Use this if you need to build robust machine learning models by easily combining preprocessing steps and learners, and want to efficiently search for the best performing pipeline structure.
Not ideal if you are new to machine learning concepts or prefer a drag-and-drop visual interface for model building rather than code-based pipeline construction.
Stars
371
Forks
29
Language
Julia
License
MIT
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
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