Deployment Using Streamlit and Heroku. Every data science aspirant, who is new to the field, has an arsenal of projects that are left untouched on their own desktops. How about we get them up on the internet??
All the code and the screenshots used in this article are from a personal project that I worked on, earlier this year. The code for the GitHub repo is linked here and the deployed model is linked here
First, you need to get streamlit installed on your system, or on the virtual environment where you’re working on this project.
If you do not have streamlit installed, open the command prompt and type:
pip install streamlit
Once you have streamlit installed, you should check out the official documentation of streamlit to familiarize yourself with the wide range of widgets provided by their python library. I will get into the following widget that I felt, are the most useful to start off with :
2. To Create a drop-down list
choices = ['1', '2', '3'] selected_ch = streamlit.selectbox('Pick a number', choices)
In this post, I will step-by-step demonstrate how to build your own Machine Learning web application that can share with your friends or colleagues, by using Streamlit and deploying it on Heroku.
Heroku is a quick and easy to use Platform as a service (PaaS) that facilitates the deployment of web apps so that it is accessible to anyone with a URL.
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