Overview
Streamlit is an open-source Python library that makes it easy to create and deploy interactive web apps for machine learning projects.
Today, you'll learn how to build simple ML app interfaces with Streamlit and understand deployment fundamentals.
Key Concepts
- Installing and setting up Streamlit
- Creating interactive widgets (buttons, sliders, inputs)
- Displaying data, charts, and model outputs
- Structuring Streamlit apps
- Running apps locally and understanding deployment options
- Basic app layout and customization
Practice Exercise
Exercise: Build a Simple ML Model Interface with Streamlit
- Install Streamlit and create a new Python script.
- Load a pre-trained ML model (e.g., from sklearn).
- Create input widgets to accept user input features.
- Display model predictions dynamically based on inputs.
- Run your Streamlit app locally and test it.
- Optionally, customize your app’s layout and style.
Resources
Streamlit Official Documentation
Main resource for today
Streamlit Tutorial for Beginners
Step-by-step guide to build your first Streamlit app
Deploying Streamlit Apps
Learn how to deploy Streamlit apps on popular platforms
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