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Versioning ML Models & Automating ML Pipelines Effectively using DVC & CML | #dvc
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In this video for complete beginners, I'll teach you about Data Version Control (DVC), a tool for adapting Git version control to machine learning projects.
DVC and CML are the tools that help us in versioning and automating the Machine Learning models and complete end-to-end pipelines. This video illustrates the demonstration of the complete end-to-end machine learning pipeline using DVC involving data and model versioning.
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Drop me mail if you need any help,
Tags:
DVC,CML,Data Version Control,Continuous Machine Learning,Model Versioning,Automating ML Pipelines,CI/CD for Deep Learning Project,CI/CD for ML Project,Data Versioning Python,Deep Learning,Data Science,version control,data science,machine learning,dvc,gitops,github,gitlab,best practices,version control best practices,version control software,open source,version control tutorial,version control in data science,git for data science,git for data scientists
#dvc #ml #datascience
DVC and CML are the tools that help us in versioning and automating the Machine Learning models and complete end-to-end pipelines. This video illustrates the demonstration of the complete end-to-end machine learning pipeline using DVC involving data and model versioning.
Follow me on below social media,
To know more about me,
Drop me mail if you need any help,
Tags:
DVC,CML,Data Version Control,Continuous Machine Learning,Model Versioning,Automating ML Pipelines,CI/CD for Deep Learning Project,CI/CD for ML Project,Data Versioning Python,Deep Learning,Data Science,version control,data science,machine learning,dvc,gitops,github,gitlab,best practices,version control best practices,version control software,open source,version control tutorial,version control in data science,git for data science,git for data scientists
#dvc #ml #datascience
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