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.
Este curso forma parte de Programa especializado: Machine Learning Engineering for Production (MLOps)
Ofrecido Por

Acerca de este Curso
• Some knowledge of AI / deep learning
• Intermediate Python skills
• Experience with any deep learning framework (PyTorch, Keras, or TensorFlow)
¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negociosHabilidades que obtendrás
- 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)
¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negociosOfrecido por
Programa - Qué aprenderás en este curso
Week 1: Model Serving: Introduction
Week 2: Model Serving: Patterns and Infrastructure
Week 3: Model Management and Delivery
Week 4: Model Monitoring and Logging
Reseñas
- 5 stars71,72 %
- 4 stars20,25 %
- 3 stars3,37 %
- 2 stars2,53 %
- 1 star2,10 %
Principales reseñas sobre DEPLOYING MACHINE LEARNING MODELS IN PRODUCTION
It's intense, applied, concrete and to the point. A very good course.
The part I enjoyed most about this course is its real-life projects which one can apply directly in business scenarios
The most practical course for junior MLOPs engineers looking for the best productionization methodologie, and the tools that implement them.
Really enjoyed it however to get he most out of it, the time commitment is large
Acerca de Programa especializado: Machine Learning Engineering for Production (MLOps)

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