Leveraging vector embeddings and LLMs for enhanced financial analysis: dash application for Central Bank documents
De Benedicts, Simone (A.A. 2023/2024) Leveraging vector embeddings and LLMs for enhanced financial analysis: dash application for Central Bank documents. Tesi di Laurea in Machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 52. [Master's Degree Thesis]
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Abstract/Index
Theoretical foundations. Natural language processing (NLP). NLP history. Feature selection and preprocessing. Deep NLP. Natural language generation (NLG) and LLM. GPT. Information retrieval. System architecture and model integration. Application workflow. Knowledge base and data preprocessing. LLM and RAG algorithm. Front end.
References
Bibliografia: pp. 50-52.
| 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: | Machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Thesis Co-Supervisor: | Simeone, Antonio |
| Academic Year: | 2023/2024 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 09 Jan 2025 08:30 |
| Last Modified: | 09 Jan 2025 08:30 |
| URI: | https://tesi.luiss.it/id/eprint/40829 |
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