Fangyang's repositories
alphalens
Performance analysis of predictive (alpha) stock factors
AlphaNet
Stock factor mining with CNN and GRU.
Book-Mathmatical-Foundation-of-Reinforcement-Learning
This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."
Books
Some special ebooks
c-binance-future-quant
低成本，高效率，简单实现的币安合约量化系统架构
gmcache
掘金量化数据API缓存加速库
Introduction-to-Golang
【未来服务器端编程语言】最全空降golang资料补给包（满血战斗），包含文章，书籍，作者论文，理论分析，开源框架，云原生，大佬视频，大厂实战分享ppt
LTSLAM
You can learn slam step by step，there are lot of tutorials
machine-learning-for-trading
Code for Machine Learning for Algorithmic Trading, 2nd edition.
moco
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
multidim-positional-encoding
An implementation of 1D, 2D, and 3D positional encoding in Pytorch and TensorFlow
nautilus_trader
A high-performance algorithmic trading platform and event-driven backtester
nomicon
The Dark Arts of Advanced and Unsafe Rust Programming
okx
Python OKX API interface
orderbook
Matching Engine for Limit Order Book in Golang
polars_ta
Technical Analysis Indicators for polars
practical_rllib_tutorial
Practical tutorial on RLlib for deep hierarchical multi-agent reinforcement learning
pykan
Kolmogorov Arnold Networks
python-polars-the-definitive-guide
Scripts and datasets for the O'Reilly book Python Polars: The Definitive Guide
QuantsPlaybook
量化研究-券商金工研报复现
rust-course
“连续六年成为全世界最受喜爱的语言，无 GC 也无需手动内存管理、极高的性能和安全性、过程/OO/函数式编程、优秀的包管理、JS 未来基石" — 工作之余的第二语言来试试 Rust 吧。<<Rust语言圣经>>拥有全面且深入的讲解、生动贴切的示例、德芙般丝滑的内容，甚至还有JS程序员关注的 WASM 和 Deno 等专题。这可能是目前最用心的 Rust 中文学习教程 / Book
rust-data-analysis
Rust for data analysis encyclopedia (WIP).
spectre
GPU-accelerated Factors analysis library and Backtester
spider-study
Learn python spider technique. 学习python的爬虫技术
tianshou
An elegant PyTorch deep reinforcement learning library.
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
x-trend
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies