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wizcap's Projects

aitextgen icon aitextgen

A robust Python tool for text-based AI training and generation using GPT-2.

asnw icon asnw

A high performance asynchronous network programming library base on libev and in c

auto-gpt icon auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

binance-triangular-arbitrage icon binance-triangular-arbitrage

Binance Triangular Arbitrage will check for each triangular arbitrage combination based on a given currency and execute three consecutive trades that result in the specified profit margin.

bitcoin-trader-rl icon bitcoin-trader-rl

A profitable cryptocurrency trading environment using deep reinforcement learning and OpenAI's gym

blackbird icon blackbird

Blackbird Bitcoin Arbitrage: a long/short market-neutral strategy

ccminer icon ccminer

CUDA miner project, compatible with most nvidia cards

clip icon clip

Contrastive Language-Image Pretraining

cnn icon cnn

Using fastai and CNNs to predict stock prices

commissionjunction-python-lib icon commissionjunction-python-lib

A python script to retrieve commission details from CJ if you are a publisher. This can be used to make internal revenue reports.

crypto-arbitrage-framework icon crypto-arbitrage-framework

A cryptocurrency arbitrage framework implemented with ccxt and cplex. It can be used to monitor multiple exchanges, find a multi-lateral arbitrage path which maximizes rate of return, calculate the optimal trading amount for each pair in the path given flexible constraints, and execute trades with multi-threading implemenation.

crypto-rl icon crypto-rl

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

cryptocurrencytrader icon cryptocurrencytrader

A machine learning program in python to generate cryptocurrency trading strategies using deep reinforcement learning on price. Keras and Tensorflow.

dall-e icon dall-e

PyTorch package for the discrete VAE used for DALL·E.

deeplob-deep-convolutional-neural-networks-for-limit-order-books icon deeplob-deep-convolutional-neural-networks-for-limit-order-books

This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.

drlformm icon drlformm

This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model"

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