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DavideCarne/README.md

Hi there 👋

  • Graduated Mathematical Engineer with a focus on Artificial Intelligence and Data Science
  • Passionate about implementing mathematical models to solve real-world problems.
  • Constantly learning and seeking improvements from latest methodologies.

🎓 Education

  • MSc in Mathematical Engineering - Major in Statistical Learning @ Politecnico di Milano
  • BSc in Mathematical Engineering @ Politecnico di Milano
  • Technical Institute - Computer Science @ Enrico Fermi Mantova

✅ Some projects i developed during my studies:

  • 📊 Statistics & Data Analysis

  • 🤖 Machine Learning & AI

    • Neural Networks for Image Recognition and Image Segmentation
    • Recurrent Neural Networks for Multivariate Time Series Forecasting
    • Generative Adversarial Networks and Variational Autoencoders for Image Generation

  • 📈 Finance & Quantitative Modeling

    • Black Box Portfolio Replication using Statistical and ML techniques

💻 Technical Skills:

C++ C Python R LaTex

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  1. bayesmix bayesmix Public

    Forked from eugeniovaretti/bayesmix

    Flexible Bayesian nonparametric mixture models in C++

    C++

  2. pgmpy pgmpy Public

    Forked from pgmpy/pgmpy

    Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

    Python

  3. PM10_BAYESIAN PM10_BAYESIAN Public

    Forked from eugeniovaretti/PM10_BAYESIAN

    Clustering spatial time series via Bayesian nonparametrics. Bayesian Statistic, MSc Mathematical Engineering, PoliMi, a.y 2022/2023

    TeX

  4. streaming-data-analytics streaming-data-analytics Public

    Forked from DarioVernola/streaming-data-analytics

    Streaming Data Analytics course material

    Jupyter Notebook