Pinned Repositories
apex
Build, deploy, and manage AWS Lambda functions with ease.
CenterNet-FSM-R
CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
darknet
YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
DCNv2
Deformable Convolutional Networks v2 with Pytorch
IT_book
本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）
mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
paper_code
After the article is published, the code will be published
pytorch-summary
Model summary in PyTorch similar to `model.summary()` in Keras
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
Sdy344's Repositories
Sdy344/CenterNet-FSM-R
Sdy344/mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
Sdy344/paper_code
After the article is published, the code will be published
Sdy344/Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
Sdy344/sdy_blog.github.io
Sdy344/CS-Notes
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
Sdy344/DCNv2
Deformable Convolutional Networks v2 with Pytorch
Sdy344/darknet
YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Sdy344/IT_book
本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）
Sdy344/pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
Sdy344/pytorch-summary
Model summary in PyTorch similar to `model.summary()` in Keras
Sdy344/PyTorch_Tutorial
《Pytorch模型训练实用教程》中配套代码
Sdy344/apex
Build, deploy, and manage AWS Lambda functions with ease.
Sdy344/TorchSnooper
Debug PyTorch code using PySnooper
Sdy344/pytorchviz
A small package to create visualizations of PyTorch execution graphs