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How to Use DevOps Azure to Create CI and CD Pipelines?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, we will discuss DevOps, two phases of DevOps, its advantages, and why we need DevOps along with CI and CD Pipelines. The post How to Use DevOps Azure to Create CI and CD Pipelines? appeared first on Analytics Vidhya.

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How Can a DevOps Team Take Advantage of Artificial Intelligence?

Analytics Vidhya

DevOps and artificial intelligence are covalently linked, with the latter being driven by business needs and enabling high-quality software, while the former improves system functionality as a whole. The DevOps team can use artificial intelligence in testing, developing, monitoring, enhancing, and releasing the system.

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How is MLOps Different from DevOps?

Analytics Vidhya

Introduction DevOps practices include continuous integration and deployment, which are CI/CD. MLOps talks about CI/CD and ongoing training, which is why DevOps practices aren’t enough to produce machine learning applications. The post How is MLOps Different from DevOps? appeared first on Analytics Vidhya.

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Bring DevOps To Data Science With MLOps

Analytics Vidhya

MLOps is the intersection of Machine Learning, DevOps and Data. The post Bring DevOps To Data Science With MLOps appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon.

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Are Your Embedded Analytics DevOps-Friendly?

Does your analytics solution work with your current tech stack and DevOps practices? Learn the 5 elements of a DevOps-friendly embedded analytics solution. If not, any update to the analytics could increase deployment complexity and become difficult to maintain.

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MLOps vs DevOps: Let’s Understand the Differences?

Analytics Vidhya

Introduction In this article, we will be going through two concepts MLOps and DevOps. As you might be aware in DevOps we try to bring together […]. The post MLOps vs DevOps: Let’s Understand the Differences? We will first try to get through their basics and then we will explore the differences between them.

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Is DataOps more than DevOps for data?

Dataconomy

DataOps and DevOps are collaborative approaches between developers and IT operations teams. The trend started with DevOps first. This communication and collaboration approach was then applied to data processing.

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