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Machine Learning experiments and engineering with DVC

Machine Learning experiments and engineering with DVC

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[DEPRECATED] The course materials are outdated and will not be updated later on. The course uses DVC 1.0 version, however new DVC 2.x versions bring new cool features. Thanks for joining us and giving very useful feedback! We are looking forward to building new FREE online courses with new DVC features and use cases. Until this, we keep this course here. You still may find this course useful and support us by buying this course. Stay in touch!

Online video course to teach basics for Machine Learning experiment management, pipelines automation and CI/CD to deliver ML solutions into production. During these lessons you ll discover basic features of Data Version Control (DVC), how it works and how it may benefit your Machine Learning and Data Science projects.

During this course listeners learn engineering approaches in ML around a few practical examples. Screencast videos, repositories with examples and templates to put your hands dirty and make it easier apply the best features in your own projects.

After this course you will be able to

Use DVC for data and artifacts version control

Build reproducible machine learning pipelines

Manage Machine Learning experiments

Automate pipelines configuration

Organize code in Machine Learning projects

Setup CI/CD pipelines with GitLab / GitHub and DVC

Specification: Machine Learning experiments and engineering with DVC

Duration

5 hours

Year

2020

Level

Intermediate

Certificate

Yes

Quizzes

No

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Machine Learning experiments and engineering with DVC
Machine Learning experiments and engineering with DVC

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