meta-learning

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

Automated Machine Learning with scikit-learn

A PyTorch Library for Meta-learning Research

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

FSL-Mate: A collection of resources for few-shot learning (FSL).

Implementation of papers in 100 lines of code.

Repository for few-shot learning machine learning projects

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

[TPAMI 2023] LibFewShot: A Comprehensive Library for Few-shot Learning.

Collection for Few-shot Learning

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

A dataset of datasets for learning to learn from few examples

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Manipulating Python Programs

Awesome Multitask Learning Resources

TorchOpt is an efficient library for differentiable optimization built upon PyTorch.