ACEMS thanks UQ Chief Investigator Dirk Kroese and his co-authors for making their book available for free download on the ACEMS website in 2020.

“The book, “Data Science and Machine Learning: Mathematical and Statistical Methods”, is intended for people interested in Mathematics and Statistics who want to look ‘under the hood’ of machine learning and data science algorithms,” said Dirk, who is a Professor of Mathematics at The University of Queensland.

The textbook targets students interested in understanding the Mathematics and Statistics that underpin a variety of ideas and Machine Learning algorithms being used now in Data Science. It contains an extensive list of exercises, worked-out examples, and many concrete algorithms with Python code.

Dirk says the book is aimed at students with a university-level background in Mathematics.

“They need not know any Data Science or Machine Learning to start with. Moreover, we cover all the maths and stats prerequisites in the appendix, as well as programming in Python,” said Dirk.

“The algorithms and code can be experimented with without knowing the full mathematical details.”

Starting from an easy undergraduate level, the book builds to an advanced, postgraduate level.

“The exercises are challenging and are there to help the student dive deeply into the material, possibly with the help of an instructor,” said Dirk.

This textbook is the seventh book that Dirk has authored, or co-authored. His research interests are in Monte Carlo methods, rare-event simulation, the cross-entropy method, applied probability, and randomised optimisation.

Dirk’s team of co-authors included Dr Zdravko Botev, the 2019 Australian Mathematical Science Institute (AMSI) Lecturer in Data Science and Machine Learning at UNSW. Dr Botev was the 2018 recipient of the Australian Academy of Science’s Christopher Heyde Medal for distinguished research in the Mathematical Sciences.

The other two co-authors are Dr Thomas Taimre and Dr Radislav (Slava) Vaisman, who are both Lecturers of Mathematics and Statistics at The University of Queensland and Associate Investigators with ACEMS.