curso
Developing Machine Learning Models for Production
Intermedio
Actualizado 2/2025Comienza el curso gratis
Incluido conPremium or Teams
TheoryMachine Learning4 horas13 vídeos44 ejercicios2,850 XP5,174Certificado de logros
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Probar DataCamp for BusinessPreferido por estudiantes en miles de empresas
Descripción del curso
Experiment and Document with Ease
Experimenting with ML models is often enjoyable but can be time-consuming. Here, you will learn how to design reproducible experiments to expedite this process while writing documentation for yourself and your teammates, making future work on the pipeline a breeze.Build MLOps Models For Production
You will learn best practices for packaging and serializing both models and environments for production to ensure that models will last as long as possible.Scale Up and Automate your ML Pipelines
By considering model and data complexity and continuous automation, you can ensure that your models will be scaled for production use and can be monitored and deployed in the blink of an eye.Once you complete this course, you will be able to design and develop machine learning models that are ready for production and continuously improve them over time.
Prerrequisitos
MLOps ConceptsSupervised Learning with scikit-learn1
Moving from Research to Production
2
Ensuring Reproducibility
3
ML in Production Environments
4
Testing ML Pipelines
Developing Machine Learning Models for Production
Curso Completo
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Inscríbete ahoraÚnete a más 15 millones de estudiantes y empezar Developing Machine Learning Models for Production hoy
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Al continuar, acepta nuestros Términos de uso, nuestra Política de privacidad y que sus datos se almacenan en los EE. UU.