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Jk's Projects

algorithm_interview_notes-chinese icon algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

awesome-cs-books icon awesome-cs-books

经典编程书籍大全,涵盖:计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等

cs-notes icon 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 icon darknet

Windows and Linux version of Darknet Yolo v3 & v2 Neural Networks for object detection (Tensor Cores are used)

deeplearning-500-questions icon 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

fpn.pytorch1.0 icon fpn.pytorch1.0

Feature pyramid network (FPN) with online hard example mining (OHEM)

fucking-algorithm icon fucking-algorithm

手把手撕LeetCode题目,扒各种算法套路的裤子,not only how,but also why. English version supported!

git_notes icon git_notes

web前端工程师 -前后端交互技术 Git和GitHub详解(完) ----学习笔记

ircnn icon ircnn

Learning Deep CNN Denoiser Prior for Image Restoration (CVPR, 2017)

labelimg icon labelimg

🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images

mish icon mish

Mish: A Self Regularized Non-Monotonic Neural Activation Function

mmdetection_visualize icon mmdetection_visualize

visualize training result for mmdetection 訓練文件可視化, PR curve绘制, F1-score计算

netron icon netron

Visualizer for neural network, deep learning and machine learning models

pothole-detection-3 icon pothole-detection-3

Deep Learning based Pothole Detection Solution. Visit https://pothole.ml or https://www.linkedin.com/feed/update/urn:li:ugcPost:6498400891610099712 to know more.

pothole_detection_on-_roads icon pothole_detection_on-_roads

An AI driven tool which identifies the number of potholes on a road and will be mapping roads in India as Good , average or bad using crowd-sourced data.

pytorch-handbook icon 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

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