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popey's Projects

agriculture_knowledgegraph icon agriculture_knowledgegraph

农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策

ailearning icon ailearning

AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

akshare icon akshare

AKShare is an elegant and simple financial data interface library for Python, built for human beings! 开源财经数据接口库

alphasickle icon alphasickle

多因子指数增强策略/多因子全流程实现

ashare icon ashare

股票行情实时数据接口-A股,完全免费的沪深证券股票数据-**股市,python最简封装的API接口,包含日线,历史K线,分时线,分钟线,全部实时采集,系统包括新浪腾讯双数据核心采集获取,自动故障切换,STOCK数据格式成DataFrame格式,可用来查询研究量化分析,股票程序自动化交易系统.为量化研究者在数据获取方面极大地减轻工作量,更加专注于策略和模型的研究与实现。

awesome-c-cn icon awesome-c-cn

C 资源大全中文版,包括了:构建系统、编译器、数据库、加密、初中高的教程/指南、书籍、库等。

awesome-cpp-cn icon awesome-cpp-cn

C++ 资源大全中文版,标准库、Web应用框架、人工智能、数据库、图片处理、机器学习、日志、代码分析等。由「开源前哨」和「CPP开发者」微信公号团队维护更新。

awesome-programming-books icon awesome-programming-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

awesome-python-cn icon awesome-python-cn

Python资源大全中文版,包括:Web框架、网络爬虫、模板引擎、数据库、数据可视化、图片处理等,由伯乐在线持续更新。

chinese-bert-wwm icon chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm系列模型)

cppnet icon cppnet

Cross platform network library with C++11

crypto-hft-data icon crypto-hft-data

Collect real-time orderbook, trade and other HFT data from several crypto exchanges using WebSocket connections.

dive-into-dl-pytorch icon dive-into-dl-pytorch

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。

efinance icon efinance

efinance 是一个可以快速获取基金、股票、债券、期货数据的 Python 库,回测以及量化交易的好帮手!🚀🚀🚀

efvicap icon efvicap

erfvicap is a packet capture tool for network adapters from Solarflare

exchange-core icon exchange-core

Ultra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.

gpt4all icon gpt4all

gpt4all: an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue

hft-exchange icon hft-exchange

A POC of an simple order exchange.Deployed on several servers gateway/dispathcer for OTC/matchingEngine/marketdataserver

hft-orderbook icon hft-orderbook

Limit Order Book for high-frequency trading (HFT), as described by WK Selph, implemented in Python3 and C

high-frequency-data-order-book-analyser icon high-frequency-data-order-book-analyser

If you are professionals, retailers or even organisms trading on a financial market, you know that data given on online platforms is not precise enough. Banks and huge financial institutions use powerful computers to transact a large number of orders at very fast speed. Thus, thousands of buying and selling orders are launched within a fraction of a second. So why can’t you see it? High Frequency Data analyser, is an innovative program helping you to analyze high frequency data in order to increase your understanding of the market. High Frequency Data takes trading to the next level, transforming your order book into a interactive visual map. You can now observe visual trading patterns and create new trading strategies. You can chose the parameters you are interested in. ( Volume/askBid). You can observe executed orders and analyse the impact of these executions on the market. You can pause and save the graph whenever you want in order to study more deeply a situation. It plays real time information and offers you many indicators to get an accurate vision of the market.(market indicator) You can visualize the available shares for each value with a very deep order book. (avancer dans le order book). You can also export your data into Excel and draw your most significant graphs. For a deeper and precise order book analysis, download High Frequency Data analyser now!

hikyuu icon hikyuu

Hikyuu Quant Framework 基于C++/Python的开源量化交易研究框架

hs300 icon hs300

沪深300指数纯因子组合构建

iocp-server icon iocp-server

A reusable TCP/IP server library that utilizes Windows I/O Completion Port (IOCP).

listed-company-news-crawl-and-text-analysis icon listed-company-news-crawl-and-text-analysis

从新浪财经、每经网、金融界、**证券网、证券时报网上,爬取上市公司(个股)的历史新闻文本数据进行文本分析、提取特征集,然后利用SVM、随机森林等分类器进行训练,最后对实施抓取的新闻数据进行分类预测

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