Information Technology Basics
Fundamental principles and concepts
Model Deployment and Maintenance for Data Scientists
The machine learning pipeline doesn't end at just building the model. This course will teach you how to deploy your machine learning models as application programming interface (API) endpoints, and the maintenance required to support the model.
Pluralsight Teams₹4,166.75 per user/month, billed annually
₹50,004
CompleteBilled Monthly
₹2,370/mo
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Course Insight
Suitable for intermediate learners. Works well as a continuation after mastering Information Technology fundamentals. It bridges the gap toward advanced, production-level engineering.
Intermediate FriendlySelf-Paced Learning
SKILLS TO
MASTER
Practical ApplicationTrending
Real-world project implementationBest Practices
Industry standard workflows and guidelinesCareers:Relevant for professionals pursuing roles within Information Technology.
Quick Facts
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What You’ll Learn
- Course Overview : 1min.
- Packaging and Deploying Your Model : 25mins.
- Monitoring and Maintaining Your Model : 11mins.
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Description
Machine learning models only become useful once they begin to support the business through a deployed application.
In this course, Model Deployment and Maintenance for Data Scientists, you'll gain the ability to run, monitor, and optimize machine learning models in production.
First, you'll explore options for deploying machine learning models as an API endpoint.
Next, you'll discover metrics and KPIs for the model you will need to monitor.
Finally, you'll learn how to iterate and improve on your model as time goes on.
When you're finished with this course, you'll have the skills and knowledge of deploying and maintaining machine learning models needed to productionalize your machine learning pipeline.
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