Sometimes you make a data science , machine learning or computer vision projects but suddenly you stuck with a thought that how to show it to the world, what type of clear technology I can use, so that everyone can see and understand your model.
Then here comes the Streamlit web framework.
What is streamlit?
Streamlit is an open-source app framework for creating and deploying data science applications. Streamlit helps data scientists and machine learning engineers to develop applications in a few hours.
Best resources to learn streamlit.
Often confused about resources, don't worry streamlit forum has made it very easy for you.
You can check their blogs, where they have arranged and covered everything you need to know about it.
Getting started with streamlit.
Create your first streamlit app.
1) Create new python file with first_app.py
2) Import libraries.
import streamlit as st # To make things easier later, we're also importing numpy and pandas for # working with sample data. import numpy as np import pandas as pd
3)Run your app
streamlit run first_app.py
For more information visit their documentation Doc
What streamlit can do?
1)Streamlit supports several popular data charting libraries like Matplotlib, Altair, deck.gl, and more.
2)With st.map() you can display data points on a map, which is really useful.
3)with st.sidebar() you can move your widget into a sidebar.
Create a model using streamlit.(Uber pickups in NYC)
Uber pickup analysis
Hope you like this post.