Learn how to implement DevOps for Data Science in this series
In this blog, we are going to discuss the Importance and usage of DevOps for Data Science. we are going to discuss terms like: What is DevOps? What are the Fundamentals Of DevOps? DevOps Lifecycle What is Data Science? Data Science Lifecycle Why do Data Scientists and DevOps need to ...
For Data Science, I find this progression works best – taking these one step at a time, and building on the previous step – the entire series is here: \n \n Infrastructure as Code (IaC) \n Continuous Integration (CI) and Automated Testing \n Continuous Deli...
Damian 与 Microsoft 的 Paige Bailey 以及 MVP Terry McCann 就 DevOps 进行数据科学会谈。 这两 个真正受欢迎的领域并不经常合并,但有一些奇妙的机会,交叉授粉的想法。 Damian、Paige 和 Terry 讨论了数据科学家的重要内容 ,以及开发运营流程的开始位置。 从使用 源代码管理、测试和刷新预测模型到操作和评估生产...
Why data scientists shouldn’t have to handle model serving The simplest answer here is that model serving is an infrastructure problem, not a data science problem. You can see this by just comparing the stacks used for each: Model development vs. model deployment ...
Edge computing integration.As the need for real-time data processing grows, integrating edge computing with DevOps practices becomes essential. This integration allows organizations to deploy and manage applications closer to data sources, reducing latency and improving performance. ...
Looking first at the CI/CD cycle for data science and analytics we can see that:. The build activities occur as sprints where models (and reports, dashboards, scorecards, etc.) are built and trained. Unit testing and user testing are integral parts of each sprint and depend on test aut...
The Gaia Science Operations Centre (SOC) is an integral part of a large consortium responsible for the Gaia data processing task. Serving terabytes of processed data on a daily basis to other Processing Centres across Europe makes unique demands on the processes, procedures, as well as the team...
The next part in this series will be focussing on Data Architecture. Hope you liked this quick insight into DevOps practices, and good luck for your data engineering adventures!本系列的下一部分将重点介绍数据架构。希望您喜欢这种对 DevOps 实践的快速见解,并祝您的数据工程冒险好运!
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