zsm191 Goto Github PK

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本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

100-days-of-ml-code

100-Days-Of-ML-Code中文版

cfnet

CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching（CVPR2021）

cfpnet

A pytorch-based real-time segmentation model for autonomous driving

cs230-code-examples

Code examples in pyTorch and Tensorflow for CS230

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被60多个国家的400多所大学用于教学。

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

dl_met

eat_pytorch_in_20_days

Pytorch🍊🍉 is delicious, just eat it! 😋😋

free-programming-books-zh_cn

:books: 免费的计算机编程类中文书籍，欢迎投稿

grok-1

Grok open release

linux_easy_tool

一个简易的个人Linux服务器ssh管理面板(webSSH&webSFTP)

mfds-detr

[CIBM] Accurate Leukocyte Detection Based on Deformable-DETR and Multi-Level Feature Fusion for Aiding Diagnosis of Blood Diseases

msnet-m2snet

(MICCAI 2021) Automatic Polyp Segmentation via Multi-scale Subtraction Network

pycinrad

Decode CINRAD (China New Generation Weather Radar) data and visualize.

pytorch-handbook-6.29-

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

safa-

WACV2024 - Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

smt

This is an official implementation for "Scale-Aware Modulation Meet Transformer".

torch-template-for-deep-learning

Pytorch Implementations of large number classical backbone CNNs, data enhancement, torch loss, attention, visualization and some common algorithms.

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

vgg

The intelligent fault diagnosis of HNU IDG

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

x-transformers

A simple but complete full-attention transformer with a set of promising experimental features from various papers