mxdlyh

GANFORCWRU

New GAN models in dataset of CWRU

GT-GAN

RTSGAN

TimeGAN-pytorch

Pytorch implementation of the paper "Time-series Generative Adversarial Networks".

ganhacks

starter from "How to Train a GAN?" at NIPS2016

TimeGAN

Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019

PyTorch-GAN

PyTorch implementations of Generative Adversarial Networks.

GAN

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

the-gan-zoo

A list of all named GANs!

CatGAN-bearing-faults

Implementation of categorical generative adversarial networks for unsupervised bearing fault diagnostics

llm_interview_note

主要记录大语言大模型（LLMs） 算法（应用）工程师相关的知识及面试题

CVPR2024-Papers-with-Code

CVPR 2024 论文和开源项目合集

deepALplus

This is a toolbox for Deep Active Learning, an extension from previous work https://github.com/ej0cl6/deep-active-learning (DeepAL toolbox).

awesome-active-learning

Everything you need about Active Learning (AL).

pytorch_active_learning

PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book

deep-active-learning

Deep Active Learning

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

PFLlib

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

LearnAug-UDA

Official implementation of Learnable Data Augmentation for Unsupervised Domain Adaptation (LearnAug-UDA)

UnsupervisedSelectiveLabeling

[ECCV 2022] Official Implementation for Unsupervised Selective Labeling for More Effective Semi-Supervised Learning

HIT-dataset

This is a dataset of inter-shaft bearing based on the vibration signal of rotors and casings, which comes from a aero-engine test with inter-shaft bearing fault. Due to the large size of the data set file, we uploaded the dataset to Google Drive with the link as: https://drive.google.com/drive/folders/1Km1Go4ilB_bI033SBJ7eJ0uCzbqEqbgt?usp=sharing

Awesome-Federated-Machine-Learning

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

hands-dirty-nlp

本课程面对具有一定机器学习基础，但尚未入门的NLPer或经验尚浅的NLPer，尽力避免陷入繁琐枯燥的公式讲解中，力求用代码展示每个模型背后的设计**，同时也会带大家梳理每个模块下的技术演变，做到既知树木也知森林。

juicy-bigdata

🎉🎉🐳 Datawhale大数据处理导论教程 | 大数据技术方向的开篇课程🎉🎉

whale-anno

Datawhale自研数据标注工具

llm-universe

本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/

self-llm

《开源大模型食用指南》基于Linux环境快速部署开源大模型，更适合**宝宝的部署教程

so-large-lm

大模型基础: 一文了解大模型基础知识

llms-from-scratch-cn

仅需Python基础，从0构建大语言模型；从0逐步构建GLM4\Llama3\RWKV6， 深入理解大模型原理

LLMs-from-scratch

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step