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Best 8 Data Version Control Tools for Machine Learning 2024

DagsHub

Released in 2022, DagsHub’s Direct Data Access (DDA for short) allows Data Scientists and Machine Learning engineers to stream files from DagsHub repository without needing to download them to their local environment ahead of time. This can prevent lengthy data downloads to the local disks before initiating their mode training.

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How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

With proper unstructured data management, you can write validation checks to detect multiple entries of the same data. Continuous learning: In a properly managed unstructured data pipeline, you can use new entries to train a production ML model, keeping the model up-to-date.

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How to Version Control Data in ML for Various Data Sources

The MLOps Blog

Dolt LakeFS Delta Lake Pachyderm Git-like versioning Database tool Data lake Data pipelines Experiment tracking Integration with cloud platforms Integrations with ML tools Examples of data version control tools in ML DVC Data Version Control DVC is a version control system for data and machine learning teams.

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How to Load and Analyze Semi-structured Data in Snowflake

phData

Here is an example of a simple XML document: 1 Scientists 1 Mike Bills Jr Scientist 234 Octopus Avenue Stamford CT 60429 2000-05-01 2000-12-01 Parquet Parquet is a file format for storing big data in a columnar storage format. It is specifically designed to work seamlessly with Hadoop and other big data processing frameworks.