100-Days-Of-ML-Code中文版

VIP cheatsheets for Stanford's CS 229 Machine Learning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes

A library of extension and helper modules for Python's data analysis and machine learning libraries.

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)

A curated list of community detection research papers with implementations.

Unsupervised Learning for Image Registration

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

Algorithms for outlier, adversarial and drift detection

A curated list of pretrained sentence and word embedding models

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

An unsupervised learning framework for depth and ego-motion estimation from monocular videos

Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)