In this session we will learn how to build an AI and Recommendations Assistant with cutting-edge features, helping users decide which Book is best suitable for their preferences. Our assistant will handle various interactions, such as, providing customized recommendations, and engaging in chat conversations. Additionally, users can register and log in to this Azure Cloud-native AI application. Microsoft Fabric will handle, automation and AI related tasks such as:

Load and clean the books Dataset with triggered Pipelines and Notebooks
Transform the Dataset to JSON and making proper adjustments for Vector usability
Load the cleaned and transformed Dataset to Azure AI Search and configuring Vector and Semantic profiles
Create and save embeddings with Azure OpenAI to Azure AI Search
As you may already guessed our foundation lies in Microsoft Fabric, leveraging its powerful Python Notebooks, Pipelines, and Datalake toolsets