2180 Repositories
Python reasoning-machine Libraries
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Deep universal probabilistic programming with Python and PyTorch
Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab
ChainerRL is a deep reinforcement learning library built on top of Chainer.
ChainerRL ChainerRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Ch
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)
Applied Reinforcement Learning @ Facebook Overview ReAgent is an open source end-to-end platform for applied reinforcement learning (RL) developed and
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,
A fast xgboost feature selection algorithm
BoostARoota A Fast XGBoost Feature Selection Algorithm (plus other sklearn tree-based classifiers) Why Create Another Algorithm? Automated processes l
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
Feature Forge This library provides a set of tools that can be useful in many machine learning applications (classification, clustering, regression, e
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
BatchFlow BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflo
Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second 🚀
What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data
cuDF - GPU DataFrame Library
cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Built based on the Apache Arrow columnar memory format,
Create HTML profiling reports from pandas DataFrame objects
Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
tensorboardX Write TensorBoard events with simple function call. The current release (v2.1) is tested on anaconda3, with PyTorch 1.5.1 / torchvision 0
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
A collection of infrastructure and tools for research in neural network interpretability.
Lucid Lucid is a collection of infrastructure and tools for research in neural network interpretability. We're not currently supporting tensorflow 2!
🎆 A visualization of the CapsNet layers to better understand how it works
CapsNet-Visualization For more information on capsule networks check out my Medium articles here and here. Setup Use pip to install the required pytho
Interpretability and explainability of data and machine learning models
AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase
A library that implements fairness-aware machine learning algorithms
Themis ML themis-ml is a Python library built on top of pandas and sklearnthat implements fairness-aware machine learning algorithms. Fairness-aware M
Python Library for Model Interpretation/Explanations
Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system
⬛ Python Individual Conditional Expectation Plot Toolbox
⬛ PyCEbox Python Individual Conditional Expectation Plot Toolbox A Python implementation of individual conditional expecation plots inspired by R's IC
FairML - is a python toolbox auditing the machine learning models for bias.
======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive
Lime: Explaining the predictions of any machine learning classifier
lime This project is about explaining what machine learning classifiers (or models) are doing. At the moment, we support explaining individual predict
A library for debugging/inspecting machine learning classifiers and explaining their predictions
ELI5 ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions. It provides support for the following m
A game theoretic approach to explain the output of any machine learning model.
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo
An intuitive library to add plotting functionality to scikit-learn objects.
Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Yellowbrick Visual analysis and diagnostic tools to facilitate machine learning model selection. What is Yellowbrick? Yellowbrick is a suite of visual
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
Contrastive Explanation (Foil Trees) Contrastive and counterfactual explanations for machine learning (ML) Marcel Robeer (2018-2020), TNO/Utrecht Univ
Bias and Fairness Audit Toolkit
The Bias and Fairness Audit Toolkit Aequitas is an open-source bias audit toolkit for data scientists, machine learning researchers, and policymakers
Algorithms for monitoring and explaining machine learning models
Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
Source-to-Source Debuggable Derivatives in Pure Python
Tangent Tangent is a new, free, and open-source Python library for automatic differentiation. Existing libraries implement automatic differentiation b
Transfer Learning library for Deep Neural Networks.
Transfer and meta-learning in Python Each folder in this repository corresponds to a method or tool for transfer/meta-learning. xfer-ml is a standalon
NLP made easy
GluonNLP: Your Choice of Deep Learning for NLP GluonNLP is a toolkit that helps you solve NLP problems. It provides easy-to-use tools that helps you l
Gluon CV Toolkit
Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in
QKeras: a quantization deep learning library for Tensorflow Keras
QKeras github.com/google/qkeras QKeras 0.8 highlights: Automatic quantization using QKeras; Stochastic behavior (including stochastic rouding) is disa
Keras community contributions
keras-contrib : Keras community contributions Keras-contrib is deprecated. Use TensorFlow Addons. The future of Keras-contrib: We're migrating to tens
Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.
Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on
Machine Learning Platform for Kubernetes
Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
Simple tools for logging and visualizing, loading and training
TNT TNT is a library providing powerful dataloading, logging and visualization utilities for Python. It is closely integrated with PyTorch and is desi
A scikit-learn compatible neural network library that wraps PyTorch
A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look
A simplified framework and utilities for PyTorch
Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne
Datasets, Transforms and Models specific to Computer Vision
torchvision The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. Installat
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
eXtreme Gradient Boosting Community | Documentation | Resources | Contributors | Release Notes XGBoost is an optimized distributed gradient boosting l
Relevance Vector Machine implementation using the scikit-learn API.
scikit-rvm scikit-rvm is a Python module implementing the Relevance Vector Machine (RVM) machine learning technique using the scikit-learn API. Quicks
TensorFlow implementation of an arbitrary order Factorization Machine
This is a TensorFlow implementation of an arbitrary order (=2) Factorization Machine based on paper Factorization Machines with libFM. It supports: d
fastFM: A Library for Factorization Machines
Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Extreme Learning Machine implementation in Python
Python-ELM v0.3 --- ARCHIVED March 2021 --- This is an implementation of the Extreme Learning Machine [1][2] in Python, based on scikit-learn. From
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
Python-based implementations of algorithms for learning on imbalanced data.
ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla
Python package for stacking (machine learning technique)
vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa
Library for machine learning stacking generalization.
stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
Automated Machine Learning with scikit-learn
auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista
Module for statistical learning, with a particular emphasis on time-dependent modelling
Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Uplift modeling and causal inference with machine learning algorithms
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
[HELP REQUESTED] Generalized Additive Models in Python
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
Metric learning algorithms in Python
metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
Machine Learning toolbox for Humans
Reproducible Experiment Platform (REP) REP is ipython-based environment for conducting data-driven research in a consistent and reproducible way. Main
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc
A toolkit for making real world machine learning and data analysis applications in C++
dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl
mlpack: a scalable C++ machine learning library --
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
PySpark + Scikit-learn = Sparkit-learn
Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear
A modular active learning framework for Python
Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe
cuML - RAPIDS Machine Learning Library
cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin
Pneumonia Detection using machine learning - with PyTorch
Pneumonia Detection Pneumonia Detection using machine learning. Training was done in colab: DEMO: Result (Confusion Matrix): Data I uploaded my datase
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python library that helps data scientists to infer causation rather than observing correlation.
Open source platform for the machine learning lifecycle
MLflow: A Machine Learning Lifecycle Platform MLflow is a platform to streamline machine learning development, including tracking experiments, packagi
🦉Data Version Control | Git for Data & Models
Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci
🗃 Open source self-hosted web archiving. Takes URLs/browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more...
ArchiveBox Open-source self-hosted web archiving. ▶️ Quickstart | Demo | Github | Documentation | Info & Motivation | Community | Roadmap "Your own pe
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
Implements Gradient Centralization and allows it to use as a Python package in TensorFlow
Gradient Centralization TensorFlow This Python package implements Gradient Centralization in TensorFlow, a simple and effective optimization technique
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework
MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.
3D Vision functions with end-to-end support for deep learning developers, written in Ivy.
Ivy vision focuses predominantly on 3D vision, with functions for camera geometry, image projections, co-ordinate frame transformations, forward warping, inverse warping, optical flow, depth triangulation, voxel grids, point clouds, signed distance functions, and others. Check out the docs for more info!
Roadmap to becoming a machine learning engineer in 2020
Roadmap to becoming a machine learning engineer in 2020, inspired by web-developer-roadmap.
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing"
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind
TensorFlow 2 AI/ML library wrapper for openFrameworks
ofxTensorFlow2 This is an openFrameworks addon for the TensorFlow 2 ML (Machine Learning) library
A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).
Rebiber: A tool for normalizing bibtex with official info. We often cite papers using their arXiv versions without noting that they are already PUBLIS
Free and Open Source Machine Translation API. 100% self-hosted, no limits, no ties to proprietary services. Built on top of Argos Translate.
LibreTranslate Try it online! | API Docs Free and Open Source Machine Translation API, entirely self-hosted. Unlike other APIs, it doesn't rely on pro
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.
Knowledge Management for Humans using Machine Learning & Tags
HyperTag HyperTag helps humans intuitively express how they think about their files using tags and machine learning.
This is where I learn machine learning
This is where I learn machine learning🤷 This means that this repo covers no specific topic of machine learning or a project - I work in here when I want to learn/try something
Contrastive Learning Inverts the Data Generating Process
Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.
MiniJVM is simple java virtual machine written by python language, it can load class file from file system and run it.
MiniJVM MiniJVM是一款使用python编写的简易JVM,能够从本地加载class文件并且执行绝大多数指令。 支持的功能 1.从本地磁盘加载class并解析 2.支持绝大多数指令集的执行 3.支持虚拟机内存分区以及对象的创建 4.支持方法的调用和参数传递 5.支持静态代码块的初始化 不支
Improving XGBoost survival analysis with embeddings and debiased estimators
xgbse: XGBoost Survival Embeddings "There are two cultures in the use of statistical modeling to reach conclusions from data