Barca0412

Introduction-to-Quantitative-Finance

量化投资学习资料整理：学界（行为金融、投资者情绪、常用程序函数，etc）；业界（公开资料整理，数据源，回测框架，卖方金工研报及复现，量化研究学习路线，etc）

Barca0412.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

gplearnplus

升级后的gplearn， 支持包含时序和截面参数的自定义函数，例如均线

awesome-obsidian

🕶️ Awesome stuff for Obsidian

Barca0412

deap

Distributed Evolutionary Algorithms in Python

Deep-Learning-Interview-Book

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

developer-roadmap

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

factor-mining_gplearn

geppy

A framework for gene expression programming (an evolutionary algorithm) in Python

gplearn

Genetic Programming in Python, with a scikit-learn inspired API

GPlearn-generate-CTA-factor

本文通过gplearn模型，结合遗传算法中的遗传规划方法生成因子。这里因子生成基于simple-backtest中的简单回测系统，主要针对股指期货操作。

gplearn_cross_factor

Enhance the gplearn package to support precise three-dimensional structured dimension genetic programming (GP), with a particular focus on enabling cross-sectional factor analysis within the package.

gplearn_stock

改进gplearn,主要使用在股票公式挖掘

gplearn_stock_dataframe

改写了gplearn源码，原有的gplearn会把数据转为numpy，丢失了datetime和stockcode的原始信息。很难做截面的因子ic、ir分析，所以改动了相应的源码，使之可以做因子的截面ic分析。另外增加了时序函数和并行化框架ray的支持

GPLearnFinance3D

对GPLearn完成了三维改造，并且增加了IC,IR,RankIC等指标，增加了样本内样本外的数据保存，增加了基于IC追踪所有generation中符合要求的因子并保存的功能。

gpquant

Mining technical factors based on symbolic regression via genetic algorithm

guohao

IT_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）

ItChat-UOS

复活Itchat,你只需要 pip install itchat-uos

ML-NLP

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

Notes-for-Quantitative-Finance

py4fi2nd

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

qlib

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Replace-sklearn-by-NumPy

scikit-learn

scikit-learn: machine learning in Python

Statistical-Learning-Method_Code

手写实现李航《统计学习方法》书中全部算法

talib-document

talib学习 talib中文翻译 talib中文文档

Cover-letter-of-Hunan-University

湖南大学的cover letter模板

zotero-style

Ethereal Style for Zotero