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(Mostly) working on narwhals
🐬
(Mostly) working on narwhals

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@hellofresh @narwhals-dev

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FBruzzesi/README.md

👋 Hi there, I'm Francesco

🦸‍♂️ About me

I am a data scientist with 5+ years of experience, a mathematician by training, a passionate learner and an open source enthusiast.

I have in depth experience working on tabular data, time series, Bayesian statistic and mathematical optimization. I tend to prefer simple, scalable and understandable solutions as opposed to over-complex models when not necessary to bring value.

💼 Employer

  • Currently, I am a data scientist at HelloFresh🍋 in Berlin office.
  • Previously I worked a senior data scientist at Edison⚡ one of the leading Italian electric utility company. Here I was involved maily on mid and down stream projects on tabular data, time series, anomaly detection, and optimization.

💻 OSS and side projects

When I have some spare time on weekends I maintain few projects:

  • Narwhals: an extremely lightweight compatibility layer between Polars, pandas, Modin, cuDF, pyarrow (and more!). I am a core maintainer since Apr. 2024. Narwhals has ~10M downloads a month.

  • scikit-lego: since Sept. 2023 I am a maintainer of the project. The goal of the package is to allow to joyfully build new building blocks that are scikit-learn compatible. scikit-lego has 20k+ downloads a month

  • ISO Week Date: iso-week-date is a toolkit to work with strings representing ISO Week date in two formats: week YYYY-WNN and week date YYYY-WNN-D.

  • Timebasedcv: a python library that provides a cross validation strategies based on actual datetime values instead of indexes, of course compatible with scikit-learn cross validation API.

  • Compclasses: a python utility library to simplify composition (over inheritance).

  • Deczoo: a zoo for python decorators, a collection of decorators used on a daily basis.

  • ATP Stats is a webapp providing tennis analytics and insights in a more colorful and intuitive manner with respect to the official ATP Tour.

📫 How to reach me

The best way it to find me on linkedin.

🔧 Tech stack

  


                


             

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  1. narwhals-dev/narwhals narwhals-dev/narwhals Public

    Lightweight and extensible compatibility layer between dataframe libraries!

    Python 611 91

  2. koaning/scikit-lego koaning/scikit-lego Public

    Extra blocks for scikit-learn pipelines.

    Python 1.3k 118

  3. timebasedcv timebasedcv Public

    Time based splits for cross validation

    Python 34 1

  4. sklearn-smithy sklearn-smithy Public

    Toolkit to forge scikit-learn compatible estimators

    Python 17

  5. iso-week-date iso-week-date Public

    Toolkit to work with str representing ISO Week date format

    Python 6