Having some free time these past weeks, I spent time exploring resources that were in my backlog. And I was astonished. So many cool — and not necessarily well known — packages on machine learning that didn’t make it to the top of the charts. Their popularity looked like niche although they cope with fundamental challenges in machine learning.
So here they are. 9 really useful packages in ML to learn and implement at work: interpretML, dtreeviz, CatBoost, plaidML, mlflow, kedro, sklearn_pandas, Streamlit, pandas_profiling.
They are presented within the following topics:
Model interpretation (interpretML, dtreeviz)
Model building (CatBoost, plaidML)
Model industrialization (mlflow, kedro, sklearn-pandas)
Apps creation (Streamlit)
Data auditing (pandas_profiling)

#data-scientist #machine-learning #data-science #machine-learning-engineer #python