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Title: Ciclo de Vida de los Datos y MLOps: Herramientas, metodologías, puesta en producción y mantenimiento de proyectos de Data Science
Author: Herrero Pascual, David
Tutor: Solé-Ribalta, Albert  
Others: Solé-Ribalta, Albert  
Abstract: This project addresses the issue of MLOps, i.e. DevOps techniques applied to Artificial Intelligence projects. The work has been written to serve as a guide for the implementation of MLOps techniques and tools at any scale, and throughout the chapters different ideas are developed to help the reader understand what MLOps is, where it comes from, why, and how it is implemented, to ultimately arrive at the implementation of a demonstration system. Specifically, after an introductory chapter, Chapter 2 presents the state of the art of DevOps and MLOps methodologies and technologies, followed by Chapter 3, which presents tools that enable the implementation of an effective methodology. Finally, in chapter 4, a test architecture is developed to demonstrate the capabilities of some of these tools, generating an automated pipeline with complete traceability from the beginning of development to production.
Keywords: data lifecycle
data science
artificial intelligence
Document type: info:eu-repo/semantics/masterThesis
Issue Date: 5-Jun-2022
Publication license:  
Appears in Collections:Bachelor thesis, research projects, etc.

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dherreropTFM0622memoria.pdfMemoria del TFM3,8 MBAdobe PDFThumbnail
dherreropTFM0622presentación.pdfPresentación del TFM1,39 MBAdobe PDFThumbnail