Howard Li's Projects
Pure python implementation of SNN
手写实现李航《统计学习方法》书中全部算法
A profitable mean reversion stock trading algorithm
A simple bash script for switching between installed versions of CUDA.
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
C#测试的一些方法或者代码块
Explore the cryptocurrency to find delta neutral strategy on correlated tokens to scalp profit through market turbulence with the expectation that their certain qualitative correlation would be bouncing in between a set of predefined ranges.
基于统计学的时间序列预测(AR,ARM).
This repository includes a range of methodologies that can be used for trading implementations as well as data analysis. The list will be updated from time to time. All the methodologies included will be written in full detail (or as detailed as it possibly can be) to avoid errors or confusion from the packages.
FlashSwap for Triangular Arbitrage on Uniswap V2 fork
Ipython notebooks for math and finance tutorials
Understanding Ethereum: Go-Ethereum Code Analysis|理解以太坊: Go-Ethereum 源码剖析
triangular arbitrage with uniswap
Volatility Arbitrage study
This is a final project done after 9 weeks Data Science Bootcamp at Le Wagon. Presented by Students Howard Li (Product Manager), Jessica Chuh (Full Stack Developer), and Jack Wu (Model Architect).
Trading Pairs are the two different types of currency that are being traded against each other. The very first trading pair you will run into as a beginner is going to be your native fiat/Bitcoin which would look like “USD/BTC” on most exchanges if you were trading in US Dollars.
Designed to create a user-friendly chatting website focusing on grouped experience. Further developments can include but are not limited to wallet authentication, social media authentication, in-room betting, live news-driven price action watching, live block buying and selling, etc
Robust Speech Recognition via Large-Scale Weak Supervision
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/