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- How to do versioning of data?
- What is meant by data versioning?
- What is a versioning strategy?
- What is data versioning in Mlops?
How to do versioning of data?
In the case of research data, a new version of a dataset may be created when an existing dataset is reprocessed, corrected or appended with additional data. Versioning is one means by which to track changes associated with 'dynamic' data that is not static over time.
What is meant by data versioning?
Data versioning is the storage of different versions of data that were created or changed at specific points in times. There are many different reasons for making changes to the data. Data scientists might test the ML models to increase efficiency and therefore make certain changes to the dataset.
What is a versioning strategy?
Versioning a product gives the consumer the option of purchasing a higher valued model for more money or a lower-valued model for less money. In this way, the business is attempting to attract higher prices based on the value a customer perceives.
What is data versioning in Mlops?
Versioning is the process of uniquely naming multiple iterations of models used at different stages of ML development to track all changes.
