Designing machine learning systems in the cloud
This course is an introduction to designing and implementing production machine learning (ML) systems that will give students the skills necessary to architect and deploy ML solutions to the cloud. This course is for anyone with at least 2 years of programming experience and familiarity with ML look...
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| Formato: | Vídeo online |
| Idioma: | Inglés |
| Publicado: |
[Sebastopol, California] :
O'Reilly Media, Inc
[2024]
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| Edición: | [First edition] |
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009843339206719 |
| Sumario: | This course is an introduction to designing and implementing production machine learning (ML) systems that will give students the skills necessary to architect and deploy ML solutions to the cloud. This course is for anyone with at least 2 years of programming experience and familiarity with ML looking to deliver real business value with ML in real, enterprise software systems. Using Python, Docker, Kubernetes, and Google Cloud, students will learn the practical skills necessary to build end-to-end ML systems, from engineering training data, features and data pipelines to deploying and monitoring ML models for real-time inference in production. |
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| Descripción Física: | 1 online resource (1 video file (1 hr., 16 min.)) : sound, color |
