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2 changes: 1 addition & 1 deletion docs/source/finrl_meta/background.rst
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Expand Up @@ -30,5 +30,5 @@ FinRL-Meta benchmarks works in famous papers and projects, covering stock tradin

DataOps
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DataOps is a series of principles and practices to improve the quality and reduce the cycle time of data science. It inherits the ideas of Agile development, DevOps, and lean manufacturing and applies them to the data science and machine learning field. FinRL-Meta follows the DataOps paradigm.

DataOps is a series of principles and practices to improve the quality and reduce the cycle time of data analytics. It inherits the ideas of Agile development, DevOps, and lean manufacturing and applies them to the data analytics field. Many implementations of DataOps have been developed in companies and organizations to improve the quality and efficiency of data analytics. These implementations consolidate various data sources, unify and automate the pipeline of data analytics, including data accessing, cleaning, analysis, visualization, and governance with a control system orchestrating, monitoring, and testing the data analytics pipeline.
6 changes: 4 additions & 2 deletions docs/source/tutorial/Guide.rst
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Expand Up @@ -11,8 +11,10 @@ Welcome to FinRL's tutorial! In this section, you can walk through the tutorial

Mission: provide user-friendly demos in notebook or python.

File Structure
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Outline

1-Introduction: basic demos for beginners.

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