프로덕션 머신러닝 시스템

Coursera MOOC / Non-credit USD 49

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About this course

이 과정에서는 프로덕션 환경에서 고성능 ML 시스템을 빌드하기 위한 구성요소와 권장사항을 자세히 살펴봅니다. 정적 학습, 동적 학습, 정적 추론, 동적 추론, 분산 TensorFlow, TPU 등 고성능 ML 시스템 빌드와 관련된 일반적인 고려사항을 다룹니다. 이 과정에서는 정확한 예측 능력 외에도 양질의 ML 시스템을 만드는 특성을 탐구하는 데 중점을 둡니다.

What you'll learn

understand the components of a high-performance ML system
implement static and dynamic learning techniques
apply distributed TensorFlow for ML applications
utilize TPUs for enhanced performance
identify best practices for quality ML system development

Skills you'll gain

production ml ml system design high-performance ml static learning dynamic learning static inference dynamic inference distributed tensorflow tpus quality attributes

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