12-08, 15:00–16:00 (UTC), Machine Learning Track
In this talk, we will cover the practical tools for modern machine learning for machine learning datasets, models, and demos. First, we will start by talking about How to Use the Hugging Face Hub, covering how to easily find the right models and datasets for your machine learning tasks. Then, we will walk through Building and Sharing ML Demos: covering how to quickly demo ML models for class presentations, portfolios, etc using the Gradio (www.gradio.dev) library.
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!
No previous knowledge expected
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 is used by more than 500,000 users every month to build learning demos. Gradio was acquired by Hugging Face, which is where Abubakar now serves as a machine learning team lead.
Abstract: In this talk, we will cover the practical tools for modern machine learning for machine learning datasets, models, and demos. First, we will start by talking about How to Use the Hugging Face Hub, covering how to easily find the right models and datasets for your machine learning tasks. Then, we will walk through Building and Sharing ML Demos: covering how to quickly demo ML models for class presentations, portfolios, etc using the Gradio (www.gradio.dev) library.
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!