Just here with a brief post on streamlit.
People who work on Data science problems usually perform feature engineering and Exploratory Data Analysis. This helps us to study how the data is spread and how it can be processed further. Most often data scientists generally do not want to spend much time in front-end development and in developing the user interface. Their main focus is to make the app functional and constantly develop it.
Streamlit has come as a boon to all the people who work in this field. It is an open-source Python library, which makes the web apps look simple but extremely satisfying.
Streamlit helps us to visualise the model and change the code accordingly side by side. It has some cool and exciting features like slider, button and many more that you should definitely check into.
Installation: pip install streamlit
Running your script: streamlit run [filename]
So what has made streamlit so popular?
• Streamlit is compatible with almost all the major libraries and frameworks.
• It helps us in building a simple API with fewer lines of code.
• Adding a widget onto the web app is also a very easy task using streamlit.
• Deploying is made pretty facile and we can host it ourselves or else we could also make use of the streamlit for teams.
Learn more through the documentation and video links given below.
Github link:- github.com/streamlit/streamlit
Documentation :- streamlit.io
Youtube Channel:- youtube.com/channel/UC3LD42rjj-Owtxsa6PwGU5Q