Coursera
MOOC / Non-credit
0
프로덕션 머신러닝 시스템
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.
D
48/100
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- What the provider tells you
- 16/45
- Who stands behind it
- 20/35
- How complete the listing is
- 12/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
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
Machine Learning
#production ml
#ml system design
#high-performance ml
#static learning
#dynamic learning
#static inference
#dynamic inference
#distributed tensorflow
#tpus
#quality attributes
$49.00
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