Architecture Reimplementation · Jupyter Notebook
Jax-Based-Random-Forest-and-Isolation-Forest
What it is
The repository implements Random Forest and Isolation Forest from scratch using JAX, including data preprocessing, multi‑GPU sharding, stump‑based and recursive tree ensembles, and evaluation against a heuristic label, with saved model pickles for reuse.
Merit describes the code at this commit. Later pushes count once the owner rescans. How merit is scored
Where it counts
- Machine Learning90%
- Data Science60%
How much of the project is about each field, as scoring counts it. It ranks in the field it is most about.
Around it on the Machine Learning board
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