Explore some of the most fundamental algorithms which have stood the test of time and provide the basis for innovative solutions in data-driven AI. Learn how to use the R language for implementing various stages of data processing and modelling activities. Appreciate mathematics as the universal language for formalising data-intense problems and communicating their solutions. These lecture notes are for you if you're yet to be fluent with university-level linear algebra, calculus and probability theory or you've forgotten all the maths you've ever learned, and are seeking a gentle, albeit thorough, introduction to the topic.
This repository hosts the HTML version of the lecture notes. You can read it at:
- https://lmlcr.gagolewski.com/ (a browser-friendly version)
- https://lmlcr.gagolewski.com/lmlcr.pdf (PDF)
Marek Gagolewski is currently a Senior Lecturer in Applied AI at Deakin University in Melbourne, VIC, Australia and an Associate Professor in Data Science (on long-term leave) at the Faculty of Mathematics and Information Science, Warsaw University of Technology, Poland and Systems Research Institute of the Polish Academy of Sciences.
His research interests include machine learning, data aggregation and clustering, computational statistics, mathematical modelling (science of science, sport, economics, etc.), and free (libre) data analysis software (stringi, genieclust, among others).
Copyright (C) 2020-2022, Marek Gagolewski.
This material is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).