Running StreamLit in Google CoLab (10.1)

This video explores how to use Streamlit to build interactive web applications for generative AI. It walks through the creation of a StreamLit app, showcasing how to use the platform’s features to input data, visualize outputs, and manage application state. The video demonstrates key concepts such as how to use StreamLit's layout, widgets, and dynamic reactivity, providing a hands-on guide for building practical applications in Python. Code for This Video: https://github.com/jeffheaton/app_generative_ai/blob/main/t81_559_class_10_1_streamlit.ipynb ~~~~~~~~~~~~~~~ COURSE MATERIAL ~~~~~~~~~~~~~~~ 📖 Textbook - Coming soon 😸🐙 GitHub - https://github.com/jeffheaton/app_generative_ai ▶️ Play List - https://www.youtube.com/watch?v=FBmUxUt__rM&list=PLjy4p-07OYzui0nVZzMgoLBeXjG9Oy3hi&ab_channel=JeffHeaton ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.heatonresearch.com/ 🐦 Twitter - https://twitter.com/jeffheaton 😸🐙 GitHub - https://github.com/jeffheaton 📸 Instagram - https://www.instagram.com/jeffheatondotcom/ 🦾 Discord: https://discord.gg/3bjthYv ▶️ Subscribe: https://www.youtube.com/c/heatonresearch?sub_confirmation=1 ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/jeffheaton 🙏 Other Ways to Support (some free) - https://www.heatonresearch.com/support.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #Streamlit #GenerativeAI #PythonProgramming #AIApplications #WebApps #DataScience #MachineLearning #AI #Python #InteractiveApps #StateManagement #WebDevelopment #T81559