Pinned Repositories
abu
阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构
awesome-cpp
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
azerothcore-wotlk
AZeroThCore - Continuing Sunwell Core Project! Based on MaNGOS -> TrinityCore -> SunwellCore
caffe-face
This branch is developed for deep face recognition
caffe-mobilenet
A caffe implementation of mobilenet's depthwise convolution layer.
CenterNetCPP
centerNet Caffe inference CPP
CSBook
Data-Analysis
Data Science Using Python
faceLandmark106
faceLandmark106
freeopcua
Open Source C++ OPC-UA Server and Client Library
Sun-ch122's Repositories
Sun-ch122/faceLandmark106
faceLandmark106
Sun-ch122/abu
阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构
Sun-ch122/awesome-cpp
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
Sun-ch122/azerothcore-wotlk
AZeroThCore - Continuing Sunwell Core Project! Based on MaNGOS -> TrinityCore -> SunwellCore
Sun-ch122/Book
:green_book:我的个人书籍学习和收藏
Sun-ch122/caffe-face
This branch is developed for deep face recognition
Sun-ch122/caffe-mobilenet
A caffe implementation of mobilenet's depthwise convolution layer.
Sun-ch122/CenterNetCPP
centerNet Caffe inference CPP
Sun-ch122/CSBook
Sun-ch122/Data-Analysis
Data Science Using Python
Sun-ch122/freeopcua
Open Source C++ OPC-UA Server and Client Library
Sun-ch122/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
Sun-ch122/qtkaifajingyan
自己总结的这十年来做Qt开发以来的经验，以及Qt相关武林秘籍电子书，会一直持续更新增加，欢迎各位留言增加内容或者提出建议，谢谢！
Sun-ch122/shadowsocks
shadowsocks.wiki
Sun-ch122/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
Sun-ch122/Surface-Defect-Detection
📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.