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.
Ce cours fait partie de la Spécialisation Machine Learning Engineering for Production (MLOps)
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À propos de ce cours
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
Votre entreprise pourrait-elle bénéficier de la formation des employés à des compétences recherchées ?
Essayez Coursera pour les affairesCompétences que vous acquerrez
- 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)
Votre entreprise pourrait-elle bénéficier de la formation des employés à des compétences recherchées ?
Essayez Coursera pour les affairesOffert par
Programme de cours : ce que vous apprendrez dans ce cours
Week 1: Model Serving: Introduction
Week 2: Model Serving: Patterns and Infrastructure
Week 3: Model Management and Delivery
Week 4: Model Monitoring and Logging
Avis
- 5 stars71,61 %
- 4 stars20,33 %
- 3 stars3,38 %
- 2 stars2,54 %
- 1 star2,11 %
Meilleurs avis pour DEPLOYING MACHINE LEARNING MODELS IN PRODUCTION
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.
A wonderful course to get started with MLOps. I have really enjoyed reading through all of its contents
À propos du Spécialisation Machine Learning Engineering for Production (MLOps)

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