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In this tutorial, we continue from our previous video on creating a FastAPI application for managing a books dataset. We delve into building a frontend using Streamlit, a simple and efficient Python tool for creating web applications. The video covers initializing the virtual environment, setting up the backend with FastAPI, and designing the frontend with multiple pages including a home page, book finder, and dashboard. Additionally, we demonstrate integrating a JSON data source, creating interactive elements like dropdowns and sliders, and making API calls to display and filter book data. By the end of the video, viewers will have a basic understanding of creating a multi-page Streamlit application that consumes a FastAPI backend. Github repo https://github.com/AIgineerAB/machine_learning_course/tree/main/09_streamlit_frontend Previous video on FastAPI https://www.youtube.com/watch?v=hheq0d0NRj8 #streamlit #fastapi #fullstack 00:00 Introduction and Recap 01:20 Setting Up the Backend 03:56 Creating the Frontend Structure 05:43 Building the Home Page 10:42 Developing the Book Finder 19:15 Designing the Dashboard 26:21 Enhancing Navigation 29:29 Conclusion and Next Steps