Andreas Mueller
Software Engineer at Microsoft
Los Gatos, California, United States
Summary
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RockstarAndreas Mueller is a Principal Research SDE at Microsoft and a scikit-learn core developer with 15 years of experience building machine learning libraries and developer tooling. He blends research-grade ML knowledge with pragmatic engineering, contributing to core projects like scikit-learn, scikit-image and nbconvert while improving reproducibility through OpenML and tooling work. Andreas places a strong emphasis on developer experience and reliability — refactoring algorithms, enhancing documentation build systems and autosummaries, and hardening testing across Python versions. He also writes educational notebooks and small utilities (including the widely used word_cloud and ML book notebooks), demonstrating a rare mix of production code, tooling, and pedagogy.
15 years of coding experience
Stackoverflow
28,118reputation
2.8mreached
252answers
21questions
classification
top-1%
conda
top-1%
scikit-learn
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python
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machine-learning
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anaconda
top-1%
Github Skills (66)
documentations10
python10
image-processing10
testing10
regression10
linear-programming10
markdown10
wordcloud10
scikit10
wordcloud210
pandas10
pi10
numpy10
computer-vision10
data-visualization10
Programming languages (25)
Github contributions (5)
dabl/dabl
Sep 2018 - Dec 2022
Data Analysis Baseline Library
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:3 releases, 3 reviews, 302 commits in 4 years 4 months
Contributions summary:Andreas primarily contributed to the development of a data analysis library by implementing and improving plotting functions and tools for machine learning. They focused on creating exploration plots for regression and classification tasks, including enhancements like improved categorical feature visualization and the incorporation of outlier handling. The user demonstrated expertise in analyzing datasets from openML datasets and also worked on model development and evaluation within the library, by building pipelines with preprocessing steps.
exploratory-data-analysisdata-analysisdata-science
pystruct/pystruct
May 2012 - Sep 2021
Simple structured learning framework for python
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:1 release, 1038 commits, 20 PRs in 9 years 5 months
Contributions summary:Andreas's primary contributions involved implementing and refining machine learning algorithms for structured prediction within the pystruct framework. They worked on several key features, including latent-variable methods, integrating the "ad3" solver, and contributing to the design of the API. This is further substantiated by their focus on developing and testing model components.
pythonstructuredframeworkmachine-learningframework-learning
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