2021-10-21 –, Data
Live broadcast: https://www.youtube.com/watch?v=EV7SkhRxemA
How can you show what a Machine Learning model does once it's trained? In this talk, you're going to learn how to create Machine Learning apps and demos using Streamlit and Gradio, Python libraries for this purpose. Additionally, we'll see how to share them with the rest of the Open Source ecosystem. Learning to create graphic interfaces for models is extremely useful for sharing with other people interesting with them.
How can you show what a Machine Learning model does once it's trained? In this talk, you're going to learn how to create Machine Learning apps and demos using Streamlit and Gradio, Python libraries for this purpose. Additionally, we'll see how to share them with the rest of the Open Source ecosystem. Learning to create graphic interfaces for models is extremely useful for sharing with other people interesting with them.
Some demo examples are:
- https://huggingface.co/spaces/flax-community/dalle-mini
- https://huggingface.co/spaces/flax-community/chef-transformer
- https://huggingface.co/spaces/nielsr/LayoutLMv2-FUNSD
Omar Sanseviero is a Machine Learning engineer with 7 years of experience. Currently he works at Hugging Face in the Open Source team democratizing the usage of Machine Learning. Previously, Omar worked as a Software Engineer at Google in the teams of Assistant and TensorFlow Graphics. Omar is passionate towards education and co-founded AI Learners, a Spanish-speaking community of people that want to learn about AI and its different applications.