SEO Short Description (2–3 lines): Pavel Pscheidl is a software engineer and writer focused on Kubernetes, cloud-native systems, and machine learning. He shares practical insights on operating complex applications, H2O machine learning platforms, and distributed systems through hands-on technical articles and tutorials.
5 articles from this blog
Explores the benefits of using Rust programming language to build high-performance, reliable Kubernetes operators for automating application management.
A guide to deploying the H2O machine learning platform on Kubernetes using Helm charts to simplify complex YAML configuration.
A guide to deploying and understanding H2O's distributed machine learning platform on a Kubernetes cluster, focusing on its stateful architecture.
H2O version 3.28.0.1 introduces parallel grid search for faster, concurrent hyperparameter tuning in distributed machine learning.
Explains how to import, inspect, and use H2O's MOJO models for scoring and analysis within the H2O platform.
