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matteosisti/README.md

👋 Hi there, I'm Matteo!

🎓 I'm currently pursuing an MSc in Data Science & Engineering at Politecnico di Torino.
💻 I'm passionate about Machine Learning, Data Engineering, and building smart solutions to solve real-world problems.

🚀 Right now, I'm focusing on developing side projects to sharpen my skills and improve the quality of my work — from APIs and automation workflows to ML-driven insights.

🌐 Connect with Me

⚡ Tech & Tools I Use

  • Languages: Python, SQL, C++
  • Data: Pandas, NumPy, Scikit-learn, XGBoost
  • APIs & Backend: FastAPI, Flask, REST
  • ML & AI: Time Series Forecasting, NLP, Recommender Systems & Ranking

"Always building, always learning."

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  1. news-article-classification-robust-ensembles news-article-classification-robust-ensembles Public

    A robust news article classification system combines a two-stage linear analysis of SEO-driven editorial style features with an independent embedding-based semantic analysis using transformer ensem…

    Jupyter Notebook

  2. neural-ranking-under-noise neural-ranking-under-noise Public

    Two-Tower BPR recommender system trained on MovieLens 20M with noise robustness analysis. Investigates how random vs popularity-biased label corruption affects ranking quality across user and item …

    Jupyter Notebook

  3. mnist-digit-classifier mnist-digit-classifier Public

    PyTorch implementation of the Kaggle Digit Recognizer competition (MNIST). Includes data preprocessing, CNN model, training loop with early stopping, scheduler, and submission pipeline.

    Jupyter Notebook

  4. Retail-Demand-Forecasting-with-LightGBM Retail-Demand-Forecasting-with-LightGBM Public

    Practical Competition on Kaggle Store Sales - Time Series Forecasting https://www.kaggle.com/competitions/store-sales-time-series-forecasting

    Jupyter Notebook