Machine Learning. A First Course for Engineers and Scientists, Hardback/***

This coherent introduction to machine learning for readers with a background in basic linear algebra, statistics, probability, and programming is suitable for advanced BSc or MSc courses. It covers theory and practice of basic and advanced methods such as deep learning, Gaussian processes, random forests, support vector machines and boosting. Publisher: Cambridge University Press Author(s): Thomas B. (Uppsala Universitet, Sweden) Schoen Illustration(s): Worked examples or Exercises Number of pages: 350 Publication date: 2022 Dimensions: 183 x 260 x 22 Cover type: Hardback