CodeCutTech/Data-science
Collection of useful data science topics along with articles, videos, and code
ArchivedCovers MLOps fundamentals (dependency management, CI/CD, data drift detection), data pipeline tools (dbt, DVC), and Python ecosystem practices (testing with pytest, dataframe optimization with Polars). Each article pairs hands-on code repositories and video tutorials with explanations of modern tools like Hydra for configuration, pre-commit hooks for automation, and GitHub Actions for ML deployment. Content spans infrastructure, testing, visualization, and LLM integration across distributed compute frameworks (Pandas, Spark, Dask).
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