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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 anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

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.

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

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

Unsupervised Learning for Image Registration

Algorithms for outlier, adversarial and drift detection

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

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

A curated list of community detection research papers with implementations.

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

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