Mazzilli, Francesco (A.A. 2023/2024) AI-driven solutions for user assistance and data analysis. Tesi di Laurea in Data science in action, Luiss Guido Carli, relatore Alessio Martino, pp. 57. [Master's Degree Thesis]

Full text for this thesis not available from the repository.

Abstract/Index

Theoretical background on generative artificial intelligence. Fundamentals of AI. Transformer architecture: the core of modern AI. How transformers work. Generative AI models: mechanisms and answer generation. Integrating the proposed chatbot. The application and general technical information. Technical implementation. UI and Functionality. Data visualization and analysis features. User assistance. Retrieval-augmented generation. Embedder. ChromaDB. Image detection. AI model. Understanding function calling in Gemini. Implementation of function calling in the assistance chatbot. Prompt engineering. Data analysis. Data analysis and SQL query generation. Predictive modeling and target variable selection. Graph identification and data visualization. Analysis module flowchart. Results. Embedder model. Image detection. Gemini evaluation. SQL queries. Prophet. Performances. System efficacy and key achievements.

References

Bibliografia: pp. 56-57.

Thesis Type:	Master's Degree Thesis
Institution:	Luiss Guido Carli
Degree Program:	Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91)
Chair:	Data science in action
Thesis Supervisor:	Martino, Alessio
Thesis Co-Supervisor:	Italiano, Giuseppe Francesco
Academic Year:	2023/2024
Session:	Extraordinary
Deposited by:	Alessandro Perfetti
Date Deposited:	10 Jul 2025 10:47
Last Modified:	10 Jul 2025 10:47
URI:	https://tesi.luiss.it/id/eprint/42872

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