Building a Machine Learning Web Application Using Streamlit

An easy tutorial on building Streamlit machine learning applications

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If you are a data scientist or data science student, you know how machine learning works. You know the details of the algorithms, which libraries to use, and perform diagnostics. Let’s say that in a business environment, you have the perfect model in your hands, with excellent results and ideal everything. Then what? It is indeed tempting to suggest that we just hand over the code to the relevant stakeholders and ask them to run it if they want to see results. But that is not how a business environment works. One solution to this problem is by creating a machine learning web application. With this solution, stakeholders can access and run your machine learning model through a website instead of some code they don’t understand.

In my previous tutorial, I demonstrated creating an ML app using Flask, a commonly used web framework in Python.

Building a Machine Learning Web Application Using Flask

Unfortunately, I realised that many data scientists lack the necessary web design…