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QKeras: a quantization deep learning library for Tensorflow Keras

A library of metrics for evaluating recommender systems

No description.

We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.

Module for statistical learning, with a particular emphasis on time-dependent modelling

Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Python package for Bayesian Machine Learning with scikit-learn API

This library has moved to https://github.com/googleapis/google-cloud-python/tree/main/packages/pandas-gbq

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Directions overlay for working with pandas in an analysis environment

Python implementation of the rulefit algorithm

scikit-learn inspired API for CRFsuite

optimization routines for hyperparameter tuning

Marsyas - Music Analysis, Retrieval and Synthesis for Audio Signals

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

A Python toolkit for processing tabular data

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

A python package for animating plots build on matplotlib.

Python library for multilinear algebra and tensor factorizations

🎆 A visualization of the CapsNet layers to better understand how it works

A set of tools for creating and testing machine learning features, with a scikit-learn compatible API

Multiple Pairwise Comparisons (Post Hoc) Tests in Python

No description.

PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

ML hyperparameters tuning and features selection, using evolutionary algorithms.

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.

An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments

Genetic feature selection module for scikit-learn