unslothai/hyperlearn
A machine learning library providing 2-2000x faster implementations of standard ML algorithms using optimized GPU and memory-efficient techniques.
Not currently ranked — collecting fresh signals.
star history
Hyperlearn is a Python library that re-implements standard machine learning algorithms to be significantly faster and more memory-efficient. It works alongside existing frameworks like scikit-learn and PyTorch, offering optimized versions of regression, TSNE, and other ML methods. The library has been incorporated into NVIDIA RAPIDS and cited in multiple academic papers for its algorithmic contributions.
Frequently asked
- What is unslothai/hyperlearn?
- A machine learning library providing 2-2000x faster implementations of standard ML algorithms using optimized GPU and memory-efficient techniques.
- Is hyperlearn open source?
- Yes — unslothai/hyperlearn is open source, released under the Apache-2.0 license.
- What language is hyperlearn written in?
- unslothai/hyperlearn is primarily written in Jupyter Notebook.
- How popular is hyperlearn?
- unslothai/hyperlearn has 2.5k stars on GitHub.
- Where can I find hyperlearn?
- unslothai/hyperlearn is on GitHub at https://github.com/unslothai/hyperlearn.