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# Assignment Proposal | ||
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## Title | ||
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_CRISP-ML(Q). The End-to-End Machine Learning Workflow_ | ||
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## Names and KTH ID | ||
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- Jacopo Maragna ([email protected]) | ||
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## Deadline | ||
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- Week 4 | ||
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## Category | ||
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- Scientific paper | ||
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## Description | ||
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The purpose of this scientific paper presentation is to guide the audience through the various phases of the machine learning workflow, as outlined in the paper ["Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology"](https://www.mdpi.com/2504-4990/3/2/20) | ||
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**Relevance** | ||
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The topics covered are particularly relevant to DevOps, especially MLOps, as they address the state-of-the-art in fully automated pipelines that handle model training, deployment to production, and performance monitoring. |