Machine Learning experiments and engineering with DVC
- 4.4
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Brief Introduction
Automate machine learning experiments, pipelines and model deployment (CI/CD, MLOps) with Data Version Control (DVC)Description
Online video course to teach basics for Machine Learning experiment management, pipelines automation and CI/CD to deliver ML solution into production. During these lessons you’ll discover base 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 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
Requirements
- Requirements
- Python
- Basic knowledge in CLI and Git is a plus
- Linux / Mac OS
Mikhail Rozhkov
4.4 Raiting
Machine Learning experiments and engineering with DVC
- 4.4
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Automate machine learning experiments, pipelines and model deployment (CI/CD, MLOps) with Data Version Control (DVC) During this course listeners learn engineering approaches in ML around a few practical examples....
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