Interesting article mostly about sharing and visualizing ML processes.

Article:

 python.plainenglish.io/5-python-libraries-every-data-scientist-should-know-about-ce04bf19d58d 

This is an article about 5 Python libraries that data scientists should know. It discusses what libraries are useful after a data scientist has chosen a machine learning library and mastered choosing the right architecture for their model. The article lists and explains 5 libraries: MLflow, Streamlit, FastAPI, XGBoost, and ELI5. Each library is introduced with a brief explanation of its purpose and benefits. The author concludes by listing the advantages of knowing these libraries. Some of the important points from this article are that these libraries can make a data scientist more competitive, help them build full-stack projects, and make their models more interpretable.