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.阅读更多.
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Deploying Machine Learning Models in Production 中涵盖的技术和工具与 数据科学家 招聘广告中的要求最为相似。
Deploying Machine Learning Models in Production is a part of 一 structured learning path.
4 Courses
4 Months
Machine Learning Engineering for Production (MLOps)
