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|Introduction to DVC: Data Version Control Tool for Machine Learning Projects | [🔗](https://codecut.ai/introduction-to-dvc-data-version-control-tool-for-machine-learning-projects-2/?utm_source=github&utm_medium=data_science_repo&utm_campaign=blog) | [🔗](https://github.com/khuyentran1401/Machine-learning-pipeline) | [🔗](https://youtu.be/80s_dbfiqLM)
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|Version Control for Data and Models Using DVC | [🔗](https://codecut.ai/introduction-to-dvc-data-version-control-tool-for-machine-learning-projects-2/?utm_source=github&utm_medium=data_science_repo&utm_campaign=blog) | [🔗](https://github.com/khuyentran1401/dvc-demo) | [🔗](https://youtu.be/80s_dbfiqLM)
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| Great Expectations: Always Know What to Expect From Your Data | [🔗](https://towardsdatascience.com/great-expectations-always-know-what-to-expect-from-your-data-51214866c24) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/data_science_tools/great_expectations_example)
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| Validate Your pandas DataFrame with Pandera | [🔗](https://medium.com/towards-data-science/validate-your-pandas-dataframe-with-pandera-2995910e564) |[🔗](https://github.com/khuyentran1401/Data-science/blob/master/data_science_tools/pandera_example/pandera.ipynb) | [🔗](https://youtu.be/CB8D7RUM-lI)
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| Introduction to Schema: A Python Libary to Validate your Data | [🔗](https://towardsdatascience.com/introduction-to-schema-a-python-libary-to-validate-your-data-c6d99e06d56a) | [🔗](https://deepnote.com/launch?url=https://github.com/khuyentran1401/Data-science/blob/master/data_science_tools/schema.ipynb)
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