semisup-learn

lijunnan1992/dividemix546

Semi-supervised learner

A PyTorch implementation of a semi-supervised learning framework for training deep neural networks with noisy labels by dynamically dividing the data into clean and noisy sets.

wohlert/semi-supervised-pytorch707

Semi-supervised models

A collection of semi-supervised learning and generative models implemented in PyTorch

tmadl/sklearn-expertsys489

Decision rule classifier

A scikit-learn wrapper for interpretable classifiers based on decision rules

wyy-123-xyy/ra-fed6

Machine learning trainer

A Python implementation of a distributed machine learning framework for training neural networks on multiple GPUs

diaoenmao/semifl-semi-supervised-federated-learning-for-unlabeled-clients-with-alternate-training36

Federated Learning System

An implementation of semi-supervised federated learning for improving the performance of a server using distributed clients with unlabeled data

ardanlabs/training-ai72

ML toolkit

Provides training materials and tools for building machine learning applications

intelligent-machine-learning/dlrover1.3K

Distributed Training System

Automates large-scale deep learning training on distributed clusters, providing fault tolerance and fast recovery from failures.

scikit-learn-contrib/metric-learn1.4K

Metric Learning Library

A Python library providing efficient implementations of various supervised and weakly-supervised metric learning algorithms.

open-mmlab/mmengine1.2K

Deep learning trainer

Provides a flexible and configurable framework for training deep learning models with PyTorch.

krayush07/learn-by-weak-supervision4

Meta-learning framework

An implementation of meta-learning from unlabeled data to improve task accuracy using a technique called 'weak supervision'

scikit-learn/scikit-learn60.5K

Machine Learning Library

A comprehensive Python module for machine learning built on top of SciPy

amueller/scipy_2015_sklearn_tutorial576

Machine Learning Tutorial

Tutorials and materials for learning machine learning with Python using popular libraries like scikit-learn.

tristandeleu/pytorch-maml-rl830

Reinforcement Learning framework

Replication of Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks in PyTorch for reinforcement learning tasks

gaelvaroquaux/scikit-learn-tutorial130

Machine Learning Tutorial

A tutorial on applying machine learning to practical situations using the scikit-learn library

sihengli99/textbind47

Conversational AI framework

Enables larger language models to generate multi-turn multimodal instruction-response conversations from image-caption pairs with minimal annotations.