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Created September 8, 2024 14:21
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CRISP-ML(Q) Framework for data science and ML project
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crisp_ml.md

Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology

  • Proposes CRISP-ML(Q), a process model for developing machine learning applications with quality assurance methodology
  • Extends CRISP-DM by adding:
    • Quality assurance methods to mitigate risks in each phase
    • A monitoring and maintenance phase post-deployment
    • Merging of business and data understanding phases
  • Provides best practices and guidelines for each phase of the ML process
  • Aims to increase success rate and efficiency of ML projects in industrial settings
  • Covers the entire ML development lifecycle, from defining objectives to maintenance

crisp_ml_table

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