yjtzsy Goto Github PK
Type: User
yjtzsy's Projects
aedificus---fathers_of_rome
A Roman themed Pygame real time strategy game
bargain-hunter-strategy
利用快均线上穿满均线抄底，效果不错
big_trend_stock
基于jqdata，均线及神仙大趋势指标选股
bulbea
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
car-manager
车辆管理系统本科毕业设计，php+mysql+python
carsystem
基于车牌识别的车辆进出管理系统
clairvoyant
Software designed to identify and monitor social/historical cues for short term stock movement
crawler-of-financial-data
从某网站获取金融数据报表并输出到CSV(包括总市值，净资产，净利润，市盈率，市净率，毛利率，净利率以及ROE。
drl
Repository for codes of 'Deep Reinforcement Learning'
glue.cal
均线粘合量化系统 by wangpj&songy
ibats_huobitrader_old
【停止维护】新版本更新已迁移到 IBATS 项目组对应名称项目中。Auto Backtest Analysis Trade Framework 支持期货、数字货币进行量化交易，集成回测、分析、交易于一体。当前项目主要用于数字货币使用。
imundboquant
Machine learning in Python for stock market and forex market predictions (fully functional)
introneuralnetworks
Introducing neural networks to predict stock prices
ma5-strategy
五日均线战法
mini-dbz
Dragon Ball game written in Python using Pygame
planewars
微信飞机大战 python pygame
predicting_stock_prices
This is the coding challenge for "Predicting Stock Prices" by @Sirajology on Youtube
proxyee-down
http下载工具，基于http代理，支持多连接分块下载
pyalgotrade
Python Algorithmic Trading Library
pyalgotrade-cn
pyalgotrade tailored for Chinese stock market
pymunk
Pymunk is a easy-to-use pythonic 2d physics library that can be used whenever you need 2d rigid body physics from Python
python
Python工程测量计算、股票数据下载分析代码
python_ranking_visualization_based_on_pygame
通过pygame实现的历史排名可视化框架，可以根据数据源将排名信息转化为动态的柱状图信息。
q-learningtradingstrategy
A project that uses Reinforcement Learning (Q-Learning) to trade stock.
q-trader
Deep Q-learning driven stock trader bot
q-trader-1
Applying Q Learning to Stock Market Data
quant
从雪球， 优矿， 聚宽获取当天的市盈率，市净率，市销率，市现率数据
quantaxis
QUANTAXIS 兼容股票和期货的 数据爬取-清洗/存储-分析/回测-可视化/交易/复盘的本地一站式解决方案
reinforcement_learning_for_stock_prediction
This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube
rl_trading
An environment to high-frequency trading agents under reinforcement learning
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