Ml Streamlit Apps

Rapidly building and deploying interactive machine learning dashboards.

jcorpac c632f4f 900 B Updated

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Streamlit ML Apps

Streamlit turns data scripts into shareable web apps in minutes. No front-end experience required.

Layout & Widgets

  • Sidebar: Use st.sidebar for controls.
  • Interactivity: Use st.slider, st.selectbox, and st.button for user input.
  • Charts: Native support for Matplotlib, Plotly, Altair, and more.

State Management

  • Session State: Use st.session_state to store values across reruns (e.g., user selections or model results).

Caching

  • Performance: Use @st.cache_data for expensive computations or data loading to ensure the app remains responsive.

Best Practices

  • UI Design: Keep it simple. Use st.markdown for rich explanations.
  • Feedback: Use st.spinner or st.progress for long-running tasks.

jcorpac/ai-skills-library/tree/main/ml/ml-streamlit-apps commit c632f4f4bd

Frequently asked questions

npx skillmds@latest add jcorpac/ml-streamlit-apps