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A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

TranslatedCurated agent skills for AI short drama, micro drama / microdrama, vertical drama and manju (AI comic drama): screenwriting, adaptation, storyboards, Seedance / Kling / MiniMax video prompts. Usable with agents such as Qwen (千问), Doubao (豆包), Lobster (龙虾) OpenClaw, WorkBuddy, Claude Code and Codex.

A curated list of threat modeling resources (Books, courses - free and paid, videos, tools, tutorials and workshops to practice on ) for learning Threat modeling and initial phases of security review.

  • threat-modeling
  • practical-devsecops
  • security-review
  • devsecops-university

Simple, fast, accurate single-header microbenchmarking functionality for C++11/14/17/20

1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy