General Machine Learning

Description

The libraries in this application area provide general-purpose machine learning functionality including preprocessing, clustering, regression, support vector classifier, K-nearest neighbors, decision trees, etc. Note that some general machine learning algorithms might not benefit from GPU acceleration as much as Deep Learning.

Projects

5

Lines Committed vs. Age Chart (click to view)

Lines Committed vs. Age Chart (click to view)

Projects

Project

Size Score

Trend Score

Byline

cuML

6.5

4.75

A suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects.

PyCaret

7.25

6.0

An open-source, low-code machine learning library in Python.

Scikit-learn

8.5

5.75

A Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.

Shogun

4.5

2.0

Shogun is an open-source machine learning library that offers a wide range of efficient and unified machine learning methods.

Smile

6.75

5.5

Statistical Machine Intelligence & Learning Engine