In christophM/interpretable-ml-book: Interpretable machine learning

Contribute to the Book {#contribute}

Thank you for reading my book about Interpretable Machine Learning. The book is under continuous development. It will be improved over time and more chapters will be added. Very similar to how software is developed.

All text and code for the book is open source and available at github.com. On the GitHub page you can suggest fixes and open issues if you find a mistake or if something is missing.

Citing this Book {#cite}

If you found this book useful for your blog post, research article or product, I would be grateful if you would cite this book. You can cite the book like this:

Molnar, C. (2022). Interpretable Machine Learning:
A Guide for Making Black Box Models Explainable (2nd ed.).
christophm.github.io/interpretable-ml-book/

Or use the following bibtex entry:

@book{molnar2022,
  title      = {Interpretable Machine Learning},
  author     = {Christoph Molnar},
  year       = {2022},
  subtitle   = {A Guide for Making Black Box Models Explainable},
  edition    = {2},
  url        = {https://christophm.github.io/interpretable-ml-book}
}

I am always curious about where and how interpretation methods are used in industry and research. If you use the book as a reference, it would be great if you wrote me a line and told me what for. This is of course optional and only serves to satisfy my own curiosity and to stimulate interesting exchanges. My mail is [e-mail] .

christophM/interpretable-ml-book documentation built on March 10, 2024, 10:34 a.m.