Getting started in building and deploying interactive data science apps with Streamlit

Flask used to come to mind when data scientists want to spin up a python-based data science app, but there is a better option now. To create an interactive facade for a machine learning or visualization script, Streamlit is way faster, since it removed the need to write any front-end code. Now we'll go through step-by-step how to build a Streamlit app. I will also review some pros and cons of Streamlit. Anyone who wants to put an interactive user interface or visible facade to the python scripts. Streamlit can be used to built machine learning/AI apps or display exploratory/analytical data visualizations or both at the same time.