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Welcome to the barefoot_winnie wiki!
This wiki contains information on the machine learning (ML) based methodology for automating the BarefootLaw recommendation system.
This wiki is organized in three main sections. Section I offers an overview of this project's pipeline. Section II contains details about the data storage and access to different layers of data. Section III discusses the raw data, data cleaning methods, and data preprocessing steps. Section IV presents the different options in the feature generation process. Section V details the machine learning methods and conducted Nearest Neighbor experiments. Finally, Section VI covers the results obtained and the generation of performance reports.
The diagram below offers an overview of the process:
For more information on this project, please refer to the Readme.