In the fourth course of Machine Learning Engineering for Production Specialization, you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case. You will also implement workflow automation and progressive delivery that complies with current MLOps practices to keep your production system running. Additionally, you will continuously monitor your system to detect model decay, remediate performance drops, and avoid system failures so it can continuously operate at all times.
Этот курс входит в специализацию ''Специализация Machine Learning Engineering for Production (MLOps)'
от партнера

Об этом курсе
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
Будет ли вашей компании выгодно обучить сотрудников востребованным навыкам?
Попробуйте Coursera для бизнесаПриобретаемые навыки
- TensorFlow Serving
- Model Monitoring
- Model Registries
- Machine Learning Operations (MLOps)
- Generate Data Protection Regulation (GDPR)
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
Будет ли вашей компании выгодно обучить сотрудников востребованным навыкам?
Попробуйте Coursera для бизнесаот партнера
Программа курса: что вы изучите
Week 1: Model Serving: Introduction
Week 2: Model Serving: Patterns and Infrastructure
Week 3: Model Management and Delivery
Week 4: Model Monitoring and Logging
Рецензии
- 5 stars71,72 %
- 4 stars20,25 %
- 3 stars3,37 %
- 2 stars2,53 %
- 1 star2,10 %
Лучшие отзывы о курсе DEPLOYING MACHINE LEARNING MODELS IN PRODUCTION
Very insightful, with a good high-level explanation of challenges surrounding model usage and deployments in a production environment.
Great course with tons of meaningful information and excellent hands-on material. Also videos and lectures and well designed and very well explained
I was hoping for a final project that I can use in my portfolio because the course content is so much and not easy to digest
It's intense, applied, concrete and to the point. A very good course.
Специализация Machine Learning Engineering for Production (MLOps): общие сведения

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