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Awesome GitHub RepositoriesConfiguration-Driven Orchestrators
Execution engines that manage complex pipelines using declarative configuration files.
Distinguishing note: Focuses on the configuration-driven nature of the orchestration engine.
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Awesome Configuration-Driven Orchestrators GitHub Repositories
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- microsoft/qlib
microsoft/qlib
37,586View on GitHubThis project is a comprehensive platform for quantitative investment research, machine learning, and algorithmic trading. It provides an end-to-end environment for developing, testing, and executing financial strategies, supporting the entire lifecycle from data ingestion and feature engineering to model training and backtesting. The system is distinguished by its configuration-driven workflow orchestration, which allows researchers to automate complex pipelines and manage experiments through declarative files. It features a high-performance data infrastructure that utilizes custom binary for
Automates complex research pipelines and experiment tracking through declarative configuration files and standardized interfaces.
Pythonalgorithmic-tradingauto-quantdeep-learning
