A Practical Tutorial on Building Machine Learning Demos with Gradio


Building machine learning demos and web apps has traditionally required significant knowledge of web development (css, js) and web hosting. We will discuss the Gradio library (www.gradio.dev), an alternative that allows you to build machine learning demos entirely in Python. This tutorial will be hands-on: we'll be going through a colab notebook and end by hosting the demo on Hugging Face Spaces, so be ready to code!

Session Outline:

Lesson 1: How to Build a Demo for your Machine Learning Model

We will look at how to build a web-based machine learning demo using your own machine learning model, entirely in Python. We'll be able to do it in about 3 lines of Python :)

Lesson 2: How to Build a Demo from a Model on the Hub

We will look at how to build a web-based machine learning demo for a pretrained model on the Hugging Face Hub. We'll be able to do it in 1 line of Python :)

Lesson 3: How to Host a Demo on Hugging Face Spaces

Once you have a demo, you might want to host it somewhere. We'll show how to host a model on Hugging Face Spaces, a process that doesn't require writing any additional code at all!

Background Knowledge:



Abubakar Abid completed his PhD at Stanford in applied machine learning. During his PhD, he founded Gradio (www.gradio.dev), an open-source Python library that has been used to build over 500,000 machine learning demos. Gradio was acquired by Hugging Face, which is where Abubakar now serves as a machine learning team lead.

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