03288nam a22005655i 4500 978-3-031-46990-9 DE-He213 20251030110859.0 cr nn 008mamaa 231226s2024 sz | s |||| 0|eng d 9783031469909 978-3-031-46990-9 10.1007/978-3-031-46990-9 doi Q325.5-.7 UYQM bicssc MAT029000 bisacsh UYQM thema Hossain, Eklas. author. aut http://id.loc.gov/vocabulary/relators/aut 68534 Machine Learning Crash Course for Engineers [electronic resource] / by Eklas Hossain. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XX, 453 p. 170 illus., 156 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Introduction to Machine Learning -- Evaluation Criteria and Model Selection -- Machine Learning Algorithms -- Applications of Machine Learning: Signal/Image Processing -- Applications of Machine Learning: Energy Systems -- Applications of Machine Learning: Robotics -- State of the Art of Machine Learning. Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of machine learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement machine learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of machine learning quickly. A concise guide to the basics of algorithms, building models, and performance evaluation; Offers highly illustrated, step-by-step guidelines with Python programming examples; Provides examples and exercises related to signal and image processing, energy systems, and robotics. Machine learning. 55059 Computational intelligence. 64052 Electrical engineering. 65586 Signal processing. Electric power production. 65675 Machine Learning. 55059 Computational Intelligence. 64052 Electrical and Electronic Engineering. 65588 Signal, Speech and Image Processing. Electrical Power Engineering. 65867 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031469893 Printed edition: 9783031469916 Printed edition: 9783031469923 https://doi.org/10.1007/978-3-031-46990-9 ZDB-2-ENG ZDB-2-SXE 56895 56895