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QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
Implementation of Axial attention - attending to multi-dimensional data efficiently
Some TrafficFlowForecasting Solutions(交通流量预测解决方案)
pytorch implemention of trajGRU.
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
Learn OpenCV : C++ and Python Examples
Volumetric Correspondence Networks for Optical Flow, NeurIPS 2019.
Simple and rapid application development framework, built on top of Flask. includes detailed security, auto CRUD generation for your models, google charts and much more. Demo (login with guest/welc…
Python Backtesting library for trading strategies
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
A curated list of awesome Flask resources and plugins
A paper list of object detection using deep learning.
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Fuzzy Logic SciKit (Toolkit for SciPy)
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great J…
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Modularized Implementation of Deep RL Algorithms in PyTorch
Minimal and Clean Reinforcement Learning Examples
Repo for the Deep Reinforcement Learning Nanodegree program
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
source code from the book Genetic Algorithms with Python by Clinton Sheppard