Honza Složil
Ředitel at Santia X Learning
Prague Metropolitan Area Czechia
Summary
🤩
Rockstar🎓
Top SchoolHonza Složil is a learning and change-management leader with 17 years’ experience blending instructional design, digital platforms and hands-on engineering sensibilities to transform corporate learning across Czechia and Slovakia. As Director of Santia and Santia X Learning he builds xLearning experiences, advises on LMS/LXP selection and drives measurable adoption using Prosci ADKAR change methodology. A former bank L&D head, he pairs strategic program design and cost-saving implementations with practical production skills—creating Articulate Storyline courses, educational videos and AI-powered multilingual avatars. Unusually for an L&D director, Honza is also a long-time Ruby developer and contributed back-end and MLOps improvements to the widely used H2O AutoML project, bringing technical credibility to machine-learning and platform integrations. His mission is to make learning clearly business‑relevant, engaging, and easy to scale.
17 years of coding experience
Mgr, Mathematics, French, Mgr, Mathematics, French at Charles University in Prague, Faculty of EducationMagistr (Mgr.), Matematika - francouzština, Magistr (Mgr.), Matematika - francouzština at Charles University
English, French
Github Skills (17)
xgboost10
machine-learning10
java10
javas10
h2o10
automl9
python8
data-science8
gbm7
cicd7
big-data7
deep-learning6
api6
data-engineer6
apim6
Programming languages (15)
Github contributions (5)
h2oai/h2o-3
Oct 2018 - Feb 2021
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:363 reviews, 65 commits, 636 PRs in 2 years 4 months
Contributions summary:Honza primarily focused on enhancing the AutoML features by adding functionality for exporting checkpoints, specifically implementing saving model checkpoints to a user-specified directory and validating the specified path. They also contributed to the XGBoost integration, incorporating checkpointing capabilities for XGBoost models. These changes included modifications to the core AutoML and XGBoost codebase, demonstrating a strong understanding of model training, saving, and loading procedures. Furthermore, the user made improvements related to hive delegation tokens for security purposes and fixes for a few bugs.
xgboostgampythonk-meansautoencoders
honzasterba/cardinity
Jan 2017 - Oct 2018
ruby wrapper for cardinity http api
Contributions:1 PR, 8 pushes, 1 branch in 1 year 9 months
ruby-wrapperapirubycardinityhttp-api
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