Preparing a dataset for fine tuning (11.2)

About this lesson

In this video, we delve into building interactive dashboards for generative AI applications using Streamlit. The tutorial walks through the steps outlined in the T81-559 course notebook, demonstrating how to create dynamic interfaces that visualize AI outputs and user interactions in real-time. We cover the integration of models into the dashboard, enabling the deployment of AI solutions in an intuitive and accessible way, perfect for both developers and non-technical users. This video is essential for those looking to bridge AI functionality with user-friendly web applications. Code for This Video: https://github.com/jeffheaton/app_generative_ai/blob/main/t81_559_class_11_2_dashboard.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 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #GenerativeAI #Streamlit #MachineLearning #AIUI #AIApplications #InteractiveDashboards #T81_559 #AIVisualization #WebDevelopment

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