Python Causal-machine-learning Resources

Feature-Engineering Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared. When the dataset

Sentiment Analysis Project This project contains two sentiment analysis programs for Hotel Reviews using a Hotel Reviews dataset from Datafiniti. The

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

Computer Vision Annotation Tool (CVAT) CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our

Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl

disentanglement_lib disentanglement_lib is an open-source library for research on learning disentangled representation. It supports a variety of diffe

Ladder Variational Autoencoders (LVAE) PyTorch implementation of Ladder Variational Autoencoders (LVAE) [1]: where the variational distributions q at

The GAN Zoo Every week, new GAN papers are coming out and it's hard to keep track of them all, not to mention the incredibly creative ways in which re

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

Human Learn Machine Learning models should play by the rules, literally. Project Goal Back in the old days, it was common to write rule-based systems.

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

Deep Metric Learning Implementation of several methods for deep metric learning in Chainer v4.2.0. Proxy-NCA: No Fuss Distance Metric Learning using P

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.

FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu

MiniSom Self Organizing Maps MiniSom is a minimalistic and Numpy based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial N

Geomstats Code Continuous Integration Code coverage (numpy) Code coverage (autograd, tensorflow, pytorch) Documentation Community NEWS: Geomstats is r

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

health-lesion-stovol healthy and lesion models for learning based on the joint estimation of stochasticity and volatility Reference please cite this p

Predicting-Tweet-Sentiment-Maching-Learning-and-streamlit (I prefere using Visual Studio Code ) Open the folder in VS Code Run the first cell in requi

Exemplary lightweight and ready-to-deploy machine learning project

The hippynn python package - a modular library for atomistic machine learning with pytorch. We aim to provide a powerful library for the training of a

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen

Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning [Project Page] [Paper] Wenlong Huang1, Igor Mordatch2, Pieter Abbeel1,

Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2

A general purpose recommender metrics library for fair evaluation.

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

High performance distributed framework for training deep learning recommendation models based on PyTorch.

Human Pose Estimation with TensorFlow Here you can find the implementation of the Human Body Pose Estimation algorithm, presented in the DeeperCut and

Simple Baselines for Human Pose Estimation and Tracking News Our new work High-Resolution Representations for Labeling Pixels and Regions is available

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

crab-knn implementation of the KNN algorithm in Python applied to biometrics data of purple rock crabs (leptograpsus variegatus) to classify the sex o

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash Abstract: Apple recently revealed its deep perceptual hashing system NeuralHash to

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

PSLA: Improving Audio Tagging with Pretraining, Sampling, Labeling, and Aggregation Introduction Getting Started FSD50K Recipe AudioSet Recipe Label E

Welcome to Official repository of deepflash2 - a deep-learning pipeline for segmentation of ambiguous microscopic images. Quick Start in 30 seconds se

CID3 This is a full-featured Decision Trees and Random Forests learner. It can save trees or forests to disk for later use. It is possible to query tr

Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control Official implementation of: Cooperative multi-agent reinfor

DeepXML Code for DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents Architectures and algorithms DeepXML supports

Recurrent Conditional Query Learning (RCQL) This repository contains the Pytorch implementation of One Model Packs Thousands of Items with Recurrent C

Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography ====== This repository contains

PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li

Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

MulMON This repository contains a PyTorch implementation of the paper: Learning Object-Centric Representations of Multi-object Scenes from Multiple Vi

Sparse Steerable Convolution (SS-Conv) Code for "Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and

Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C

A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions Kapoutsis, A.C., Chatzichristofis,

This repository contains the codebase for the paper Continual Learning via Local Module Composition. Setting up the environemnt Create a new conda env

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

deepMRI: Deep learning methods for MRI Authors: Yang Gao, Hongfu Sun This repo is devloped based on Pytorch (1.8 or later) and matlab (R2019a or later

Release of AutoGMap:Learning to Map Large-scale Sparse Graphs on Memristive Crossbar For reproduction of our searched model, the Ubuntu OS is recommen

Repo for paper "Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information" Notes I probabl

Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin

Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri

Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge Associated code for the paper Zero-Shot Learning in Named Entity Recognitio

NoCodeSeg: Deep segmentation made easy! This is the official repository for the manuscript "Code-free development and deployment of deep segmentation

On Effective Scheduling of Model-based Reinforcement Learning Code to reproduce the experiments in On Effective Scheduling of Model-based Reinforcemen

KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as

HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati

LearningPsychologicalSpaces v0.1: v1.1: v1.2: v1.3: v1.4: v1.5: The code in this repository explores learning a mapping from images to psychological s

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code

Always Be Dreaming: A New Approach for Data-Free Class-Incremental Learning PyTorch code for the ICCV 2021 paper: Always Be Dreaming: A New Approach f

Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

StableLLVE This is a Pytorch implementation of "Learning Temporal Consistency for Low Light Video Enhancement from Single Images" in CVPR 2021, by Fan

Knowledge Base Completion Meets Transfer Learning This code accompanies the paper Knowledge Base Completion Meets Transfer Learning published at EMNLP

Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

Singify Introducing Singify, the party game! Challenge your friend to who knows songs better. Play random songs from your very own Spotify playlist an

Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo

PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

scikit-survival scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizi

PySurvival What is Pysurvival ? PySurvival is an open source python package for Survival Analysis modeling - the modeling concept used to analyze or p

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.

partial_dependence A python library for plotting partial dependence patterns of machine learning classifiers. The technique is a black box approach to

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software