Explaining the Explainable: Translating “Interpretable Machine Learning” into Japanese

Explaining The Explainable: Translating “Interpretable Machine Learning” Into Japanese

Hello, everyone! I’m Ryuji Masui, Data Scientist at HACARUS R&D center in Tokyo.

HACARUS has been solving problems in the medical and manufacturing industries using our “Lightweight & Explainable AI” technology. In fact, we are regularly holding internal study sessions on this topic. In these sessions, we’ve been using “Interpretable Machine Learning – A Guide for Making Black Box Models Explainable” written by Christoph Molnar as reference.

This book covers a wide range of topics related to Explainable AI with real-life examples. Firstly, Molnar touches on the definition of Explainable AI, and describes how AI should be “explained”. He also talks about model-agnostic ways to realize Explainable AI, even when using models like Deep Learning that are difficult to interpret.

I believe that it is a great guide for anyone who is interested in Explainable AI (XAI) and/or Explainability of Machine Learning models. I’d also recommend this book to people who have already used Machine Learning before, and would like to be able to tell the reasons why their models came to their conclusions.

“Interpretable Machine Learning – A Guide for Making Black Box Models Explainable” by Christoph Molnar is published under a Creative Commons license (CC BY-NC-SA 4.0). Because the book is a great reference, we’ve decided to translate its contents and publish them in Japanese. The author was very happy about our translation project too – in fact, he mentioned us in the chapter “Translations” in the original publication.

We are currently in the middle of translating – the first 3 chapters we have translated so far are already public. You can read them here.

Just like the original, the Japanese version of the book is managed on GitHub public repository. If you would like to participate in this project, please feel free to join us from here. The original version is constantly updated too – so we would appreciate any feedback or participation.

We are very excited to translate the rest of the book and share it with you – please stay tuned for more! In the meantime, I will keep publishing articles here on HACARUS’ website. It would be a great pleasure if my articles could help you in any way, with the latest information regarding the topic of Explainable AI.



HACARUS is rapidly expanding and actively hiring new talents from all over the world. If you are interested in working with a motivated and diverse team at HACARUS, please contact us here.

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Takashi Someda

CTO of Hacarus. Has over 15 years experience as a software and server engineer in several global SaaS startups. Currently working hard to make something new with machine learning. Holds masters degree in Information Science at Kyoto University.

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