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.
machine-learning
deep-learning
python
platform
research
finance
algorithmic-trading
auto-quant
fintech
investment
paper
quant
quant-dataset
quant-models
quantitative-finance
quantitative-trading
research-paper
stock-data
Обновлено 2024-11-13 06:41:06 +03:00
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
docker
reinforcement-learning
simulator
finance
inventory-management
logistics
maro
multi-agent
multi-agent-reinforcement-learning
operations-research
raas
resource-optimization
rl-algorithms
transportation
agent
citi-bike
Обновлено 2024-02-23 11:45:58 +03:00
Qlib-Server is the data server system for Qlib. It enable Qlib to run in online mode. Under online mode, the data will be deployed as a shared data service. The data and their cache will be shared by all the clients. The data retrieval performance is expected to be improved due to a higher rate of cache hits. It will consume less disk space, too.
Обновлено 2022-07-08 05:15:09 +03:00