Johan Manders
Company Owner at Sphereness
Netherlands
Summary
👤
Senior🎓
Top SchoolJohan Manders is a software architect and company owner with a decade of experience building digital products and shaping governance through his firm Oably and design-development work at Sphereness. He combines hands-on engineering—evidenced by substantive contributions to the widely used XGBoost project improving training/evaluation workflows—with leadership roles in community and personal development as chairman of Samen voor Someren and a certified coach. Comfortable spanning architecture, product design, and developer-facing machine learning tooling, Johan brings a pragmatic, user-focused approach to complex systems. His background in hypnotherapy and coaching suggests an uncommon emphasis on human-centered decision-making and team dynamics alongside technical delivery.
10 years of coding experience
Coach Foundation NOBCO-, EMCC- en EIA-erkenning, Coach Foundation NOBCO-, EMCC- en EIA-erkenning at LaudiusHypnotherapy, Hypnotherapy at NVTH
Dutch, English
Github Skills (8)
scikit-learn10
gbm10
xgboost10
machine-learning10
python10
scikit10
data-analysis9
distributed-systems8
Programming languages (6)
Github contributions (5)
dmlc/xgboost
Oct 2015 - Nov 2015
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Role in this project:
ML Engineer
ML EngineerContributions:26 commits, 4 PRs, 24 comments in 1 month
Contributions summary:Johan primarily focused on enhancing the functionality and usability of the XGBoost library's training and evaluation processes. They made significant changes to `training.py`, improving the handling of multiple evaluation metrics and fixing data mislabeling issues. Additionally, the user updated the `sklearn.py` file to ensure compatibility with the updated training results and added example code and documentation to illustrate how to access evaluation metrics from the library. This work directly contributes to improving the training and evaluation experience within the XGBoost framework.
daskdataflowgbmgradient-boostinghadoop
JohanManders/xgboost
Oct 2015 - Nov 2015
Contributions:13 PRs, 34 pushes, 7 branches in 1 month
single-nodeyarnscalelarge-scalegbdt
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