Francesco Sannicola
Machine Learning | Software Engineering
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Latest Projects
Updated on June 19, 2025
Smart Product Categorization Engine
A transformer-based text classification system for product categorization using fine-tuned BERT-like models. Implements multi-class prediction with containerized deployment for scalable and reliable use in e-commerce applications.
Updated on Mar 19, 2025
Document-Claim Evidence Mapper
A document-claim analysis tool that uses LLMs to extract and rank relevant text supporting or refuting claims. Combines prompt-based NLP with customizable evaluation for fact-checking and analysis in legal and financial contexts.
Updated on Mar 22, 2025
ML-based classification of customer complaint drivers
A data-driven approach to understand and predict customer dissatisfaction through data processing, exploratory analysis, predictive modeling, rigorous evaluation, and actionable visualization.
Updated on Sep 29, 2024
LLM-Powered Email Generation and Multi-Class Classification
Building and evaluating a machine learning pipeline for email classification utilizing synthetic data generated by a GPT-based email generator with Few-Shot Learning.
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Latest Articles
Updated on Dec 17, 2024
Understanding Random Number Generation
Exploring Random Number Generators (RNG), Linear Congruential Generators (LCG), and Permuted Congruential Generator (PCG) focusing on their mechanisms.
Updated on Mar 9, 2025
GenAI and LLM Questions with In-Depth Answers
From prompt engineering to advanced concepts, this guide demystifies large language models (LLMs) while preparing you for technical interviews with detailed, practical examples.
See All Articles
Smart Product Categorization Engine
A transformer-based text classification system for product
categorization using fine-tuned BERT-like models. Implements
multi-class prediction with containerized deployment for
scalable and reliable use in e-commerce applications.
Document-Claim Evidence Mapper
A document-claim analysis tool that uses LLMs to extract and
rank relevant text supporting or refuting claims. Combines
prompt-based NLP with customizable evaluation for fact-checking
and analysis in legal and financial contexts. 
ML-based classification of customer complaint drivers
A data-driven approach to understand and predict customer
dissatisfaction through data processing, exploratory analysis,
predictive modeling, rigorous evaluation, and actionable
visualization.
LLM-Powered Email Generation and Multi-Class
Classification
Building and evaluating a machine learning pipeline for email
classification utilizing synthetic data generated by a GPT-based
email generator with Few-Shot Learning.
Understanding Random Number Generation
Exploring Random Number Generators (RNG), Linear Congruential
Generators (LCG), and Permuted Congruential Generator (PCG)
focusing on their mechanisms.
GenAI and LLM Questions with In-Depth Answers
From prompt engineering to advanced concepts, this guide
demystifies large language models (LLMs) while preparing you for
technical interviews with detailed, practical examples.