Coursera – Machine Learning Engineering for Production (MLOps) Specialization

Coursera – Machine Learning Engineering for Production (MLOps) Specialization
English | Tutorial | Size: 1.95 GB

Become a Machine Learning expert. Productionize your machine learning knowledge and expand your production engineering capabilities.

What You Will Learn:
• Design an ML production system end-to-end: project scoping, data needs, modeling
strategies, and deployment requirements.
• Establish a model baseline, address concept drift, and prototype how to develop, deploy, and
continuously improve a productionized ML application.
• Build data pipelines by gathering, cleaning, and validating datasets. Establish data lifecycle by
using data lineage and provenance metadata tools.
• Apply best practices and progressive delivery techniques to maintain and monitor a
continuously operating production system.

Skill You Will Gain:
• Managing Machine Learning Production Systems
• Deployment Pipelines
• Model Pipelines
• Data Pipelines
• Machine Learning Engineering for Production
• Human-level Performance (HLP)
• Concept Drift
• Model baseline
• Project Scoping and Design
• ML Deployment Challenges
• ML Metadata
• Convolutional Neural Network

About this Specialization
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.

NITROFLARE
nitroflare.com/view/75FAB7B50369FF2/Coursera_-_Machine_Learning_Engineering_for_Production_%28MLOps%29_Specialization.part1.rar
nitroflare.com/view/6CE0981A12325B8/Coursera_-_Machine_Learning_Engineering_for_Production_%28MLOps%29_Specialization.part2.rar
nitroflare.com/view/8DD9BB031C0B0C1/Coursera_-_Machine_Learning_Engineering_for_Production_%28MLOps%29_Specialization.part3.rar