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awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

bert

TensorFlow code and pre-trained models for BERT

bert-chinese-text-classification-pytorch

使用Bert，ERNIE，进行中文文本分类

bert-ner

Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.

blinear-cnn-faster

A Faster PyTorch implementation of bilinear CNN for fine-grained image recognition

chinese-poetry

The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。

chinese-text-classification-pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

cogdl

CogDL: An Extensive Research Toolkit for Graphs

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

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[email protected] 版权所有，违权必究 Tan 2018.06

drawio

Source to app.diagrams.net

drawio-desktop

Official electron build of diagrams.net

face_recognition

The world's simplest facial recognition api for Python and the command line

flask_web

基于flask将一个评论分类模型嵌入到web系统中

jave

ner

命名实体识别实践与探索

nndl.github.io

《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-handbook

pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行

pytorch-image-models-multi-label-classification

Multi-label classification based on timm.

stable-diffusion

A latent text-to-image diffusion model

stopwords-iso

All languages stopwords collection

tensorflow_cookbook

Code for Tensorflow Machine Learning Cookbook

the-kaggle-book

Code Repository for The Kaggle Book, Published by Packt Publishing

timm

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.