Beginner or seasoned data scientist, I bet at some point you thought of going beyond local machine & Jupyter notebooks and releasing your data science projects into the wild.

So what’s holding you back?

There is a common perception that data scientists are unicorns who know everything — from HTML, CSS, Javascript to all sorts of software engineering tools and frameworks. But we know that’s not the case. Just because you are good at writing codes for data science problems, not necessarily you will also have web development and software engineering skills. Taking your code to production requires a completely different skillset that you may or may not have.

Now there is a shortcut in this production pipeline. You can be a great data scientist and still be able to deploy your project without having to have web development and software engineering skills.

It’s brought to you by_ Streamlit_.

What is Streamlit?

“Streamlit’s open-source app frameworkisthe easiest way for data scientists and machine learning engineers to create beautiful, performant apps in only a few hours! All in pure Python. All for free” — that explains everything you need to know in terms of definition.

In the background of all these goodies I want to warn you upfront that — Streamlit is for Pythonistas! If you are into R or another programming language, unfortunately, nothing you can do other than translating a couple of your projects into Python and exploring Streamlit and its capabilities.

Why is Streamlit revolutionary?

In public discourse we often hear buzzwords such as empowerment, empowering people etc. I think the easiest way I could describe Streamlit’s contribution to the data science field is that it is truly empowering data scientists in all fields of application.

I’ve already said it but in case it wasn’t clear enough — you don’t have to be an expert in web development or software engineering, Streamlit empowers you to turn your project into a professional-looking app with only a little marginal effort. I can almost guarantee that even if you’ve never heard of Streamlit before, you can still be able to create your first web app within the next day or two. Just give it a try!

#machine-learning #streamlit #web-app-development #data-science