by Evidence Based Machine Learning Lab

ebook: https://mini-pw.github.io/2020L-WB-Book

This book is the result of a student projects for Case Studies course at the Warsaw University of Technology. Each team prepared an article on one of the topics selected from reproducibility, imputation, and interpretability.

This project is inspired by a fantastic books Limitations of Interpretable Machine Learning Methods done at the Department of Statistics, LMU Munich and XAI Stories. Case studies for eXplainable Artificial Intelligence done at the Warsaw University of Technology and at the University of Warsaw.

We used the LIML project as the cornerstone for this repository.

Step 1: Clone or download the repository https://github.com/mini-pw/2020L-WB-Book.

Step 2: Install dependencies

devtools::install_dev_deps()

Step 3: Render the book (R commands)

# HTML
bookdown::render_book('./', 'bookdown::gitbook')
# PDF
bookdown::render_book('./', 'bookdown::pdf_book')