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GeezerVison is showing github.com — P403n1x87 - Overview

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@P403n1x87
P403n1x87
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Tinkering

Gabriele N. Tornetta P403n1x87

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🔭 MSc in Theoretical Physics 🧮 PhD in Pure Mathematics ⌨️ I write code for the fun of a new challenge 🐍 CPython contributor 🕵️ Austin creator 📚 Author
213 followers · 55 following
  • @DataDog
  • Scotland, UK
  • p403n1x87.github.io
  • @p403n1x87

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@emeryberger

Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: YOLOAchievement: QuickdrawAchievement: Starstruckx3Achievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull Sharkx4Achievement: Pair Extraordinairex4Achievement: YOLOAchievement: QuickdrawAchievement: Starstruckx3Achievement: Arctic Code Vault Contributor
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P403n1x87/README.md

Synopsis

Gabriele has a curiosity that's hard to appease. Since a early age he's always been intrigued by Science and Nature and wanted to know more about its fundamental laws. Together with his taste for abstraction as a way to find order and rigour in things, he embarked on an adventure to learn about Physics and Mathematics. He likes Technology very much too, a trait you could have guessed if you had the chance to see him crack open any gizmos he came across to see what was inside and understand how they worked.

Changelog

2016 - Upgrade to PhD Pure Mathematics

2011 - Upgrade to MSc Theoretical Physics

2009 - Upgrade to BSc Physics

1987 - Initial release

Publications

A list of all my academic publications can be found on arxiv.org.

I maintain The Hub of Heliopolis, a blog where I collect the notes of my experiments with technology.

I'm also the author of the following books

  • Mathematical Quantum Physics, A Foundational Introduction

  • The Mathematical Foundations of Machine Learning

Main Projects

Currently, my main project is Austin, a frame stack sampler for CPython which can be used to build powerful statistical profilers for Python applications that don't require instrumentation and have minimal impact on the application runtime, making it ideal for profiling in production.

Contributions

My work on Austin is helping developing the profiling interface of Python. See my contributions to CPython for more details.

Growth

I always wanted to learn about Machine Learning and in 2018 I started exploring its mathematical fundamentals. You can find my personal take in my book The Mathematical Foundations of Machine Learning.

My project Marvin collects some code that I wrote as part of my experiments and applications of ML techniques that I have used to solve certain problems.

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