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baobaojiu's Projects

alipay icon alipay

支付宝 AliPay SDK for Go, 集成简单,功能完善,持续更新。

awesome-cpp icon awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

cppbestpractices icon cppbestpractices

Collaborative Collection of C++ Best Practices. This online resource is part of Jason Turner's collection of C++ Best Practices resources. See README.md for more information.

d2l-zh icon 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。

diff icon diff

基于websocket和json的协议, 用于在期货软件系统间实现行情/交易/历史数据交互

fastapi-celery icon fastapi-celery

Example of how to handle background processes with FastAPI, Celery, and Docker

ftdcnet.ctp icon ftdcnet.ctp

.Net wrapper for ftdc2c_ctp. Support x86/x64/AnyCPU.

fushare icon fushare

A utility for fundamentals data of China commodity futures

gamedevmind icon gamedevmind

最全面的游戏开发技术图谱。帮助游戏开发者们在已知问题上节省时间,省出更多的精力投入到更有创造性的工作中去。 | The most comprehensive technical map of game development. Help game developers save time on known problems and save more energy for more creative work.

go42 icon go42

《Go语言四十二章经》详细讲述Go语言规范与语法细节及开发中常见的误区,通过研读标准库等经典代码设计模式,启发读者深刻理解Go语言的核心思维,进入Go语言开发的更高阶段。

gopay icon gopay

微信(WeChat)、支付宝(AliPay)的Go版本SDK。【持续更新,望开发者及时升级】

jqdataserviceforvnpy icon jqdataserviceforvnpy

数据服务:使用聚宽jqdatasdk获取分钟数据按vnpy的Bar格式导入至mongodb中,提供本地数据库数据校验功能

klinechart icon klinechart

📈Lightweight k-line chart that can be highly customized. Zero dependencies. Support mobile.(可高度自定义的轻量级k线图,无第三方依赖,支持移动端)

lean icon lean

Try migrate lean to .netcore.

leetcode-go icon leetcode-go

✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解

quantaxis icon quantaxis

QUANTAXIS 支持任务调度 分布式部署的 股票/期货/自定义市场 数据/回测/模拟/交易/可视化 纯本地PAAS量化解决方案

rqalpha icon rqalpha

A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities

stock-prediction-models icon stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stockpredictionai icon 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.

tedukuri icon tedukuri

《算法竞赛进阶指南》资源社区

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