Strojno učenje za inženirje: Koncepti, primeri in uporaba v okolju MATLAB - Gotlih, Janez; Brezočnik, Miran (University of Maribor Press, 2025)
Machine Learning for Engineers: Concepts, examples, and applications in MATLAB. The book deala with machine learning from the perspective of its application in engineering, linking fundamental concepts with practical application in the MATLAB environment. Four basic approaches to machine learning are presented: supervised learning, unsupervised learning, reinforcement learning, and transfer learning. For each approach, basic concepts, specific use cases, and independent work assignments are provided. Special emphasis is placed on the use of tools such as Regression Learner, Classification Learner, Deep Network Designer, and Reinforcement Learning Designer, with which students develop models based on data derived from real engineering examples. These include tool wear, machine vibrations, system balancing, and object recognition. The scripts also include experimental data sets and practical guidelines for learning, validating, and improving models. They are intended for students of technical disciplines and anyone who wants to learn how to use machine learning methods to solve specific engineering problems.