This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
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Principales reseñas sobre PRODUCTION MACHINE LEARNING SYSTEMS
This course reveals some practical techniques in Production Machine Learning Systems. I like the real world examples introduced in this course.
It is very good course, gives good overview over large ML systems on cloud, a lot of examples from real implementations gives good understunding about problematics in projects realisations
Very practical which was nice. Thank you for adding the Quicklabs that helped a lot.
I did not realize the many aspects to consider implementing a Production ML system. This course presents all of them and provides guidance for evaluating alternative
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Una vez que te inscribes y comienza la sesión, tendrás acceso a todos los videos y otros recursos, incluidos artículos de lectura y el foro de debate del curso. Podrás ver y enviar tareas de práctica y completar tareas con calificación obligatorias para obtener un título y un Certificado de curso
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¿Por qué no puedo participar como oyente en este curso?
Este curso es uno de los pocos que se ofrecen en Coursera que está actualmente disponible solo para estudiantes que pagaron o que recibieron ayuda económica, si está disponible.
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Last Updated: September 1, 2015
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