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Configurable, streamable, efficient and extensible encoding/decoding for Kotlin Multiplatform.

  • Updated Jan 10, 2026
  • Kotlin

This project predicts traffic accident severity using the 2023 STATS19 dataset. It employs machine learning and LIME to not only forecast outcomes like 'Fatal' or 'Slight' but also to provide clear, understandable explanations for its predictions, creating a powerful tool for enhancing road safety.

  • Updated Sep 13, 2025
  • Jupyter Notebook

Base64CPPLib is an open source Base64 encoding and decoding library written in “modern” C++. The library is highly extensible, and supports working with strings, hexadecimal streams, and files.

  • Updated Jan 14, 2018
  • C++

🚦 Predict traffic accident severity using advanced machine learning and explainable AI, enhancing road safety with clear insights from comprehensive data analysis.

  • Updated Mar 9, 2026
  • Jupyter Notebook

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