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| Introduction to Weight & Biases: Track and Visualize your Machine Learning Experiments in 3 Lines of Code | [🔗](https://towardsdatascience.com/introduction-to-weight-biases-track-and-visualize-your-machine-learning-experiments-in-3-lines-9c9553b0f99d) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/data_science_tools/wandb_tracking)
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| Kedro — A Python Framework for Reproducible Data Science Project | [🔗](https://towardsdatascience.com/kedro-a-python-framework-for-reproducible-data-science-project-4d44977d4f04) | [🔗](https://github.com/khuyentran1401/kedro_demo)
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| Orchestrate a Data Science Project in Python With Prefect | [🔗](https://towardsdatascience.com/orchestrate-a-data-science-project-in-python-with-prefect-e69c61a49074) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/data_science_tools/prefect_example)
| Orchestrate Your Data Science Project with Prefect 2.0 | [🔗](https://medium.com/the-prefect-blog/orchestrate-your-data-science-project-with-prefect-2-0-4118418fd7ce) | [🔗](https://github.com/khuyentran1401/analyze_github_feed)
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| DagsHub: a GitHub Supplement for Data Scientists and ML Engineers | [🔗](https://towardsdatascience.com/dagshub-a-github-supplement-for-data-scientists-and-ml-engineers-9ecaf49cc505) | [🔗](https://dagshub.com/khuyentran1401/dagshub-demo)
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| 4 pre-commit Plugins to Automate Code Reviewing and Formatting in Python | [🔗](https://towardsdatascience.com/4-pre-commit-plugins-to-automate-code-reviewing-and-formatting-in-python-c80c6d2e9f5) | [🔗](https://github.com/khuyentran1401/Data-science/tree/master/productive_tools/precommit_examples) | [🔗](https://youtube.com/playlist?list=PLnK6m_JBRVNqskWiXLxx1QRDDng9O8Fsf)
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| BentoML: Create an ML Powered Prediction Service in Minutes | [🔗](https://towardsdatascience.com/bentoml-create-an-ml-powered-prediction-service-in-minutes-23d135d6ca76) | [🔗](https://github.com/khuyentran1401/customer_segmentation/tree/bentoml_demo)
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