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  • Articles Tagged with "Model Deployment"

    Exam Professional Machine Learning Engineer topic 1 question 270 discussion - ExamTopics

    examtopics.com • Technology • World

    This question focuses on efficiently managing and deploying machine learning models within Google Cloud's Vertex AI platform, emphasizing the use of experiments and pipelines for streamlined workflows.

    Exam Professional Machine Learning Engineer topic 1 question 266 discussion - ExamTopics

    examtopics.com • Technology • World

    This article presents a multiple-choice question about deploying a retrained machine learning model for a music streaming service on Vertex AI, focusing on minimizing complexity and using A/B testing for gradual rollout.

    Exam Professional Machine Learning Engineer topic 1 question 259 discussion - ExamTopics

    examtopics.com • Technology • World

    This article presents a multiple-choice question about deploying a machine learning workflow using Google Cloud Platform services, focusing on version control, scalability, and resource optimization.

    Exam Professional Machine Learning Engineer topic 1 question 29 discussion - ExamTopics

    examtopics.com • Engineering • World

    This article presents a multiple-choice question regarding the optimal architecture for deploying a machine learning model with computationally expensive preprocessing steps on Google AI Platform.

    Exam Professional Machine Learning Engineer topic 1 question 179 discussion - ExamTopics

    examtopics.com • Engineering • World

    This article presents a machine learning engineering question about deploying an XGBoost model trained in Python for online serving using Google Kubernetes Engine and explores various approaches to efficiently implement pre- and post-processing steps.

    Exam Professional Machine Learning Engineer topic 1 question 175 discussion - ExamTopics

    examtopics.com • Technology • World

    This question discusses the optimal method for deploying a scikit-learn model to Vertex AI for both online and batch prediction, focusing on minimizing additional code.