Скачать или смотреть How To Automate AI Deployment With MLOps On Cloud? - Learning To Code With AI

How To Automate AI Deployment With MLOps On Cloud? In this informative video, we will guide you through the process of automating artificial intelligence deployment using Machine Learning Operations (MLOps) on cloud platforms. We’ll cover the essential concepts of MLOps, including its significance in managing the machine learning lifecycle from development to monitoring. By understanding the different levels of MLOps, you will learn how to implement automation effectively, making your AI projects more efficient.

We will outline the steps necessary for setting up automated pipelines that handle everything from data ingestion to model monitoring. You’ll discover how to integrate continuous integration and continuous delivery pipelines with popular code repositories, ensuring that your workflows run seamlessly. Additionally, we’ll highlight the cloud MLOps services offered by major providers, such as Google Cloud, Amazon Web Services, and Microsoft Azure, which can simplify your deployment process.

Monitoring your models after deployment is critical, and we’ll discuss how to utilize cloud monitoring tools to maintain optimal performance. Finally, we’ll share practical examples to illustrate how these concepts come together, equipping you with the knowledge to automate AI deployment effectively. Join us on this journey to streamline your AI projects, and be sure to subscribe for more content focused on coding and AI tools.

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#MLOps #MachineLearning #AIDeployment #CloudComputing #Automation #ContinuousIntegration #ContinuousDelivery #DataScience #GoogleCloud #AWS #Azure #VertexAI #SageMaker #ModelMonitoring #AIProjects #TechEducation

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