关于此 专项课程

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Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well. Effectively deploying machine learning models requires competencies more commonly found in technical fields such as software engineering and DevOps. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and engineering roles. The Machine Learning Engineering for Production (MLOps) Specialization covers how to conceptualize, build, and maintain integrated systems that continuously operate in production. In striking contrast with standard machine learning modeling, production systems need to handle relentless evolving data. Moreover, the production system must run non-stop at the minimum cost while producing the maximum performance. In this Specialization, you will learn how to use well-established tools and methodologies for doing all of this effectively and efficiently. In this Specialization, you will become familiar with the capabilities, challenges, and consequences of machine learning engineering in production. By the end, you will be ready to employ your new production-ready skills to participate in the development of leading-edge AI technology to solve real-world problems.
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高级
完成课程大约需要 4 个月
建议进度:6 小时/周
英语(English)
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
高级
完成课程大约需要 4 个月
建议进度:6 小时/周
英语(English)

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此专项课程包含 4 门课程

课程1

课程 1

Introduction to Machine Learning in Production

4.8
772 个评分
149 条评论
课程2

课程 2

Machine Learning Data Lifecycle in Production

4.5
196 个评分
36 条评论
课程3

课程 3

Machine Learning Modeling Pipelines in Production

4.6
71 个评分
14 条评论
课程4

课程 4

Deploying Machine Learning Models in Production

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deeplearning.ai

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