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Julia package for Regularized Discriminant Analysis.

Open-source package for validating ML models & data, with various checks and suites.

A Julia package for probability distributions and associated functions.

Many useful features that aren't part of the main nn package.

Python package which helps to debug machine learning classifiers and explain their predictions.

A Python package to assess and improve fairness of machine learning models.

Feature engineering package with SKlearn like functionality.

Julia package for Gaussian processes.

Python package for geospatial intelligence workflows, location data, and map-based OSINT tasks.

Unified interface to ggplot2 popular R packages.

A lightweight tool to report on the licenses used by a Go package and its dependencies. Highlight! Versioned external URL to licenses can be found at the same time.

Package for computer vision using OpenCV 4 and beyond.

A python package that integrates an LLM copilot inside the keras model development workflow.

Build, packaging, and run system for ephemeral multi-container environments.

Julia package for working with various human languages.

A Julia package for manifold learning and nonlinear dimensionality reduction.

A Julia package for fitting (statistical) mixed-effects models.

A Julia package for non-negative matrix factorization.

Nn builder is a python package that lets you build neural networks in 1 line.

This package provides graphical computation for nn library in Torch7.

A completely unstable and experimental package that extends Torch's builtin nn library.

Turns websites into lightweight desktop apps, useful for packaging web tools as simple cross-platform applications.

This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.

wireshark profiles provides Wireshark profiles or network analysis resources for packet inspection workflows.