100-days-of-ml-code

100 Days of ML Coding

500lines

500 Lines or Less

ai-homework

人工智能结课作业（A星八数码/广度优先/深度优先/粒子群寻优算法/遗传算法/蚁群算法/BP神经网络/卷积神经网络）

al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

alibi

Algorithms for monitoring and explaining machine learning models

awesome-counterfactual-explanations

awesome counterfactual explanations

awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

awesome-curiosity-learning

A curated list of awesome curiosity learning frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

awesome-explainable-ai

A collection of research materials on explainable AI/ML

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

awesome-tmux

A list of awesome resources for tmux

badminton_court_booking

Script to book badmin court on ActiveSG website.

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

build_and_test_examples

Examples of build scripts and unit test frameworks for various languages, and how these can be used with the Jenkins continuous integration server. Contact: @mikej888

c-chvae-pytorch

The reproduction of c-chvae.

cachelot

Cache library and distributed caching server. Memcached compatible.

captum

Model interpretability and understanding for PyTorch

ce7454_2019

Deep learning course CE7454, 2019

ceml

CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox

cemsp

CIKM 2023, Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations

cf-feasibility

Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"

cfai

A collection of algorithms of counterfactual explanations.

concept_exp

code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"

conference_call_for_paper

2019-2020 International Conferences in Artificial Intelligence, Machine Learning, Computer Vision, Data Mining, Natural Language Processing and Robotics

contrastive-explanation-method

deep-multimodal-speaker-naming

deep-reinforcement-learning

algorithms about deep reinforcement learning(pytorch version)

dice

Generate Diverse Counterfactual Explanations for any machine learning model.

dualcf

FaccT 2022, DualCF: Efficient Model Extraction Attack from Counterfactual Explanations