[18] Streamlit for Data Science (Thomas Fan)
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Thomas Fan: Streamlit for Data Science
Key Links
Transcript: https://github.com/data-umbrella/even...
Meetup Event: https://www.meetup.com/data-umbrella/...
Video: • [18] Streamlit for Data Science (Thomas Fan)
GitHub repo: https://github.com/thomasjpfan/data-u...
Agenda
00:00 -- Data Umbrella Introduction by Reshama --
03:46 Reshama introduces Thomas
04:37 Thomas introduces the talk
05:12 What is Streamlit?
05:40 Intro to the demos
07:16 Demo 1: Show me some penguins!
12:55 Adding plots to Streamlit
17:52 Demo 2: Train model in Jupyter Lab
20:29 Demo 3: Explanation predictions with Streamlit
23:28 Adding user input to Streamlit
27:28 Using the pre-trained model for predictions
28:36 Explaining predictions: SHAP values
30:30 Explaining predictions: Anchors
34:52 Other resources
37:01 Q: How did you get started with Streamlit?
38:14 Q: What are the key differences between Streamlit and Dash?
39:22 Q: What are other alternatives to Streamlit?
39:56 Q: Is there a time limit for the external API?
40:38 Q: Is there a async way to use Streamlit?
41:23 Q: What challenges or missing features do you see in Streamlit?
42:50 Q: What is the easiest way to deploy a Streamlit app?
44:54 Q: Is Streamlit responsive?
Event
Streamlit is an open source Python library that makes it easy to build web applications for data science and machine learning. It integrates with many plotting libraries such as matplotlib, seaborn, and plotly for showing visualizations in your application. In this talk, we develop a dashboard which introduces streamlit's features and capabilities. Afterwards, we develop a web application that integrates SHAP and anchor explanations for a model's prediction based on user input.
About the Speaker
Thomas J. Fan is a Staff Associate at the Data Science Institute at Columbia University. He is one of the core developers of scikit-learn, an open source machine learning library written in Python. He also maintains skorch, a scikit-learn compatible neural network library that wraps PyTorch. Thomas believes that developing open source software is one of the best ways to maximize one's impact.
LinkedIn: / thomasjpfan
Twitter: / thomasjpfan
GitHub: https://github.com/thomasjpfan
#python #datavisualization #dashboard