Pinned Repositories
algorithm-visualizer
:fireworks:Interactive Online Platform that Visualizes Algorithms from Code
annotated_deep_learning_paper_implementations
🧑🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
approachingalmost
Approaching (Almost) Any Machine Learning Problem
Awesome-Backbones
Integrate deep learning models for image classification | Backbone learning/comparison/magic modification project
Awesome-Chinese-NLP
A curated list of resources for Chinese NLP 中文自然语言处理相关资料
Awesome-Dataset-Distillation
Awesome Dataset Distillation Papers
awesome-explanatory-supervision
List of relevant resources for machine learning from explanatory supervision
awesome-knowledge-graph
整理知识图谱相关学习资料
Domain-LLM
收集和梳理垂直领域的开源模型、数据集及评测基准。
Enzo-MiMan.github.io
yaowuxie's Repositories
yaowuxie/awesome-knowledge-graph
整理知识图谱相关学习资料
yaowuxie/awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
yaowuxie/bert_seq2seq
pytorch实现 Bert 做seq2seq任务，使用unilm方案,现在也可以做自动摘要，文本分类，情感分析，NER，词性标注等任务,支持t5模型，支持GPT2进行文章续写。
yaowuxie/CLUENER2020
A PyTorch implementation of a BiLSTM\BERT\Roberta(+CRF) model for Named Entity Recognition.
yaowuxie/CS-Books-Store
你想要的计算机经典书籍，这里都有！
yaowuxie/CVPR2022-Paper-Code-Interpretation
cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理
yaowuxie/CVPR2022-Papers-with-Code
CVPR 2022 论文和开源项目合集
yaowuxie/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
yaowuxie/Digimon-Generator-GAN
This repo contains the code that generates Digimon images using the concept of GAN
yaowuxie/Explore-Deep-Network-Explainability-Using-an-App
This repository provides an app for exploring the predictions of an image classification network using several deep learning visualization techniques. Using the app, you can: explore network predictions with occlusion sensitivity, Grad-CAM, and gradient attribution methods, investigate misclassifications using confusion and t-SNE plots, visualize l
yaowuxie/foundations-for-analytics-with-python
yaowuxie/gan
Various GAN Model
yaowuxie/InterpretableMLBook
《可解释的机器学习--黑盒模型可解释性理解指南》，该书为《Interpretable Machine Learning》中文版
yaowuxie/Knowledge-Distillation-Zoo
Pytorch implementation of various Knowledge Distillation (KD) methods.
yaowuxie/Lhy_Machine_Learning
李宏毅2021春季机器学习课程课件及作业
yaowuxie/machine-learning-
yaowuxie/machine_learing_study
yaowuxie/named_entity_recognition
中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）
yaowuxie/NLP
✔️最全面的 深度学习NLP 笔记
yaowuxie/pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
yaowuxie/readata
Python数据分析实战项目汇总~
yaowuxie/reproducible-image-denoising-state-of-the-art
Collection of popular and reproducible image denoising works.
yaowuxie/sofasofa-learn
yaowuxie/Spider
✔️最全面的 爬虫与数据库 笔记
yaowuxie/Swin-Transformer-Object-Detection
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
yaowuxie/team-learning
主要展示Datawhale的组队学习计划。
yaowuxie/text-classification-surveys
文本分类资源汇总，包括深度学习文本分类模型，如SpanBERT、ALBERT、RoBerta、Xlnet、MT-DNN、BERT、TextGCN、MGAN、TextCapsule、SGNN、SGM、LEAM、ULMFiT、DGCNN、ELMo、RAM、DeepMoji、IAN、DPCNN、TopicRNN、LSTMN 、Multi-Task、HAN、CharCNN、Tree-LSTM、DAN、TextRCNN、Paragraph-Vec、TextCNN、DCNN、RNTN、MV-RNN、RAE等，浅层学习模型，如LightGBM 、SVM、XGboost、Random Forest、C4.5、CART、KNN、NB、HMM等。介绍文本分类数据集，如MR、SST、MPQA、IMDB、Yelp、
yaowuxie/torch-template-for-deep-learning
Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.
yaowuxie/TransReID-SSL
Self-Supervised Pre-Training for Transformer-Based Person Re-Identification
yaowuxie/vit-explain
Explainability for Vision Transformers