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๐Ÿ‘‹ Hello, I'm David Przybilla

Software Engineer - working in the Data realm (MLops, Data engineering, Infrastructure)

Working on/Interested in:

  • Python/Golang/Scala
  • ๐Ÿค– Building tools for empowering ML engineers and Data scientists
  • ๐Ÿค– Reproducibility of: Software and Machine Learning
  • ๐Ÿค– Making the ML lifecycle faster
  • ๐Ÿ‘ท Data pipelines
  • ๐Ÿ‘ท Kubernetes

๐Ÿ“ฌ

David Przybilla's Projects

streamlit icon streamlit

Streamlit โ€” The fastest way to build custom ML tools

suboptimal icon suboptimal

Seriously Unnecessary Baffling Obscure Perplexing Terms In MAchine Learning

surprise icon surprise

A Python scikit for building and analyzing recommender systems

testbook icon testbook

๐Ÿงช ๐Ÿ“— Unit test your Jupyter Notebooks the right way

tfnotify icon tfnotify

A CLI command to parse Terraform execution result and notify it as GitHub

the-personal-page icon the-personal-page

This simple one-page website is a way for people to have a very quick and easy personable website that aggregates your activity and positions a simple logo, a portrait and some description text in a nicely-formatted manner. This is licensed under the MIT and GPL licenses.

tldextract icon tldextract

Accurately separate the TLD from the registered domain and subdomains of a URL, using the Public Suffix List.

tqdm icon tqdm

A fast, extensible progress bar for Python and CLI

transformers icon transformers

๐Ÿค— Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

tre icon tre

[AKBC 19] Improving Relation Extraction by Pre-trained Language Representations

truthgraph icon truthgraph

Automatically extracted Data set of human right violations in Colombia

unionml icon unionml

UnionML: the easiest way to build and deploy machine learning microservices

vearch icon vearch

A distributed system for embedding-based retrieval

vectorsinsearch icon vectorsinsearch

Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

voila icon voila

Voilร  turns Jupyter notebooks into standalone web applications

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