Data Science and Machine Learning: Mathematical and Statistical Methods
by Dirk P. Kroese, Zdravko I. Botev, Thomas Taimre, and Radislav Vaisman

The purpose of this book is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin the rich variety of ideas and machine learning algorithms in data science.

Key Features:

• Focuses on mathematical understanding.
• Presentation is self-contained, accessible, and comprehensive.
• Extensive list of exercises and worked-out examples.
• Many concrete algorithms with Python code.
• Full color throughout.

📢 Good news!

• The first edition of this book is available free of charge for educational purposes or self-study. You are welcome to download the PDF, provided that you give due acknowledgement to the source.
• The second edition is coming soon! Click here for details and updates

In bibtex, please cite the first edition as follows:

@book{kroese2019dsml,
  title     = {Data Science and Machine Learning: Mathematical and Statistical Methods},
  author    = {D.P. Kroese and Z.I. Botev and T. Taimre and R. Vaisman},
  year      = {2019},
  publisher = {Chapman & Hall/CRC},
  address = {Boca Raton}
}

If you don’t have Git installed, download and install it from: https://git-scm.com/downloads

• Windows: During installation, select "Git Bash" when prompted. This will allow you to use Git commands easily.
• macOS: You can install Git via Homebrew with:

  brew install git

• Linux: Use your package manager, for example:

  sudo apt-get install git

After installation:

• On Windows, search for Git Bash in the Start menu and open it.
• On macOS/Linux, open your Terminal.

In the terminal or Git Bash, run:

git clone https://github.com/DSML-book/Programs.git

This will create a folder named Programs with all the files in the Programs repository.

If you don’t want to use Git, you can also download the ZIP file:

• Go to https://github.com/DSML-book/Programs
• Click the green Code button → Download ZIP
• Extract the ZIP file to your desired location.