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lucalullo/README.md

Luca Lullo - Data Scientist

Data Scientist indipendente specializzato in data analysis, data cleaning avanzato e machine learning.

Sviluppo dataset, notebook e modelli predittivi in diversi ambiti, con particolare attenzione all’analisi di dati pubblici, sistemi istituzionali e dinamiche socio-economiche. Mi occupo di integrazione di dataset eterogenei, costruzione di indicatori comparabili e sviluppo di analisi riproducibili per auditing, ricerca e supporto alle decisioni, utilizzando Python per trasformare dati complessi in informazioni affidabili e utilizzabili.

🏆 Kaggle 2x Expert

Kaggle

  • Datasets Expert: Top 100 globale (Rank 87) · 15 dataset pubblici con Usability Score 10.0
  • Notebooks Expert: Rank ~1.098 · 25+ notebook pubblicati

🛠 Stack Tecnologico

Python Pandas Scikit-learn XGBoost LightGBM CatBoost TensorFlow Keras PyTorch Plotly SQL

📂 Progetti in evidenza

Progetto Tema Strumenti & Highlights
Global Inequality and Poverty (1980–2024) Socio-Economia Data integration, indicatori globali comparabili
Italian Justice System Workload Dati Istituzionali Analisi civile/penale 2003–2024, auditing
Home Credit Default Risk Credit Risk ML XGBoost, LightGBM, SHAP, feature engineering
Global Emissions & Temperature Clima / Serie Storiche CO₂, GHG, temperature 1950–2024

📬 Contatti

LinkedIn

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  1. Customer-churn Customer-churn Public

    Customer churn prediction using Random Forest and class-weight balancing. Detailed EDA and feature engineering on telecom industry data.

    Jupyter Notebook

  2. House-prices House-prices Public

    Predicting house prices using Ridge Regression, Skewness transformation and Advanced Feature Engineering.

    Jupyter Notebook

  3. Used-car-prices Used-car-prices Public

    Machine learning project to predict used car prices with feature engineering and LightGBM.

    Jupyter Notebook

  4. Italian-justice-workload Italian-justice-workload Public

    Multidimensional analysis of the Italian justice system workload (2003–2024). A study of civil and criminal proceedings using judicial pressure and litigation indicators.

    Jupyter Notebook

  5. Home-credit-default-risk Home-credit-default-risk Public

    Machine learning project to predict credit default risk with feature engineering, XGBoost and SHAP interpretability.

    Jupyter Notebook

  6. Global-emissions-and-temperature-1950-2024 Global-emissions-and-temperature-1950-2024 Public

    Global climate analysis covering 75 years of CO₂, greenhouse gas emissions and mean surface temperatures across countries (1950–2024). Built with Pandas, Matplotlib, Seaborn and Plotly.

    Jupyter Notebook