About
Dive into the world of responsible machine learning with the RML comic/text/book. It showcases the process of developing predictive models, emphasizing validation and exploration techniques while integrating cutting-edge eXplainable Artificial Intelligence (XAI) methods.
Explore ten detailed parts, unraveling the step-by-step journey of model creation, analysis, and validation. Balancing theory, practical code examples in Python and R, and an engaging comic narrative, join Beta and Bit on their adventures to grasp the essence of model development.
Discover the thrill and depth of crafting models responsibly, making learning both insightful and enjoyable.
Fully reproducible code snippets
Immerse yourself in a story based on real analyses within the context of the COVID-19 pandemic. This book features datasets generated based on real data, ensuring that all findings and results presented are rooted in actual, tangible information.
Moreover, we prioritize reproducibility, offering complete transparency in our methodologies and providing step-by-step instructions that empower readers to replicate every analysis, model, and outcome.
The data, R and Python scripts are available at https://github.com/BetaAndBit/RML
How to get this book?
The printed version of this book with R and Python snippets is available on Amazon! Dive into the world of responsible machine learning with the convenience of a physical copy at your fingertips.
Get the book directly from Amazon https://amzn.eu/d/b0oLKF4.
You can also read the online version for free. The online version is available at https://rml.mi2.ai/.
What to do with this book?
You can use this book as a self-teaching material, it provides a comprehensive guide to understanding responsible machine learning, offering theoretical insights alongside practical code examples in Python and R. Moreover, it stands as an invaluable companion for workshops and training sessions focused on machine learning. Educators and workshop facilitators can utilize its structured approach and reproducible analyses to augment workshops, fostering in-depth discussions and hands-on learning experiences.
Language versions
This book was translated into the following languages:
- Spanish translation ,,La Guía del Viajero al Aprendizaje Automático Responsable’’ by Juan C. Correa and Yanina Bellini Saibene avaliable at https://betaandbit.github.io/RML_ES/
- German translation ,,Per Anhalter durch die Galaxis des verantwortungsvollen maschinellen Lernens’’ by Gero Szepannek avaliable at https://betaandbit.github.io/RML_DE/
- Turkish translation ,,Sorumlu Makine Öğrenmesi Rehberi’’ by Mustafa Çavuş and Özlem Kurt Çavuş avaliable at https://betaandbit.github.io/RML_TR/
- Polish translation ,,Wprowadzenie do modelowania predykcyjnego’’ by Anna Kozak, Aleksander Zawada, Hubert Baniecki and Przemysław Biecek avaliable at https://betaandbit.github.io/MiniML/
- Vietnamese translation ,,4.0.1 Cùng xây dựng Model Machine Learning với Bêta và Bít’’ by Lý Hoàng Thiên avaliable at https://betaandbit.github.io/RML_VN/
