20.500.12556/DKUM-95916 Strojno učenje za inženirje koncepti, primeri in uporaba v okolju MATLAB Machine Learning for Engineers Concepts, Examples, and Applications in MATLAB Skripta obravnavajo strojno učenje z vidika uporabe v inženirstvu, pri čemer temeljne koncepte povezujejo s praktičnimi primeri v okolju MATLAB. Predstavljeni so štirje temeljni pristopi strojnega učenja: nadzorovano učenje, nenadzorovano učenje, učenje z okrepitvijo in prenosno učenje. Za vsak pristop so podani temeljni koncepti, konkretni primeri uporabe ter naloge za samostojno delo. Poseben poudarek je na uporabi orodij, kot so Regression Learner, Classification Learner, Deep Network Designer in Reinforcement Learning Designer, s pomočjo katerih študenti razvijajo modele na podatkih, ki izvirajo iz realnih inženirskih primerov. Med njimi so obraba orodja, vibracije strojev, balansiranje sistemov in prepoznavanje predmetov. Skripta vključujejo tudi eksperimentalne podatkovne množice in praktične napotke za učenje, validacijo in izboljšavo modelov. Namenjena so študentom tehniških smeri ter vsem, ki želijo usvojiti uporabo metod strojnega učenja za reševanje konkretnih inženirskih problemov. The book deals 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. strojno učenje nadzorovano učenje nenadzorovano učenje učenje z okrepitvijo prenosno učenje MATLAB inženirske aplikacije machine learning supervised learning unsupervised learning reinforcement learning transfer learning MATLAB engineering applications true false true Univerza v Mariboru, Univerzitetna založba Slovenski jezik Angleški jezik Učbenik za višje in visoke šole 2025-11-10 12:12:21 2025-11-10 12:12:21 2025-11-11 03:08:47 0000-00-00 00:00:00 2025 0 Maribor 2025 Maribor 0000-00-00 NiDoloceno Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 978-961-299-078-7 004.42:51 256145411 10.18690/um.fs.10.2025 https://press.um.si/index.php/ump/catalog/book/1075 1 21877a1b-be26-11f0-8bb8-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=200511 RAZ_Gotlih_Janez_2025.pdf RAZ_Gotlih_Janez_2025.pdf 1 8148E50DC49D3129D544816AF5F7A819 ae00c64195e25642d6fdcd0989d4cd70f6cc8e2432c9e30c6a0df32431a46ded 7a53c578-be26-11f0-8bb8-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=200513 Fakulteta za strojništvo Univerzitetna založba Univerze v Mariboru 0 0 0