Boltzmann Machines in TensorFlow with examples

Parallel Hyperparameter Tuning in Python

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

Python bindings and scikit-learn interface for the Operon library for symbolic regression.

A sklearn style interface to Stan regression models

A simple template of a Python API (web-service) for real-time Machine Learning predictions, using scikitlearn-like models, Flask and Docker.

A tool for performing cross-validation with panel data

Contains data preprocessing and visualization methods for ADL datasets.

Polynomial regression and classification with sklearn and tensorflow

SVR for multidimensional labels

A scikit-learn-compatible module for Isolation-based anomaly detection using nearest-neighbor ensembles

Optimizers for/and sklearn compatible Machine Learning models

ParALleL frAmework for moDel selectIOn

Utilities for easy use of custom losses in CatBoost, LightGBM, XGBoost.

Scikit learn compatible constrained and robust polynomial regression in Python

Drop-in replacement of sklearn's Linear Regression with coefficients constraints

A scikit-learn-compatible module for Isolation Kernel with aNNE implemention.

XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.

A Python implementation of random vector functional networks and broad learning systems using Sklearn's Regressor and classifier APIs

Machine Learning Transition State Analysis (MLTSA) suite with Analytical models to create data on demand and test the approach on different types of data and ML models.