03500nam a22005775i 4500 978-3-031-60950-3 DE-He213 20251030112841.0 cr nn 008mamaa 240807s2024 sz | s |||| 0|eng d 9783031609503 978-3-031-60950-3 10.1007/978-3-031-60950-3 doi TA1501-1820 TA1634 UYT bicssc COM016000 bisacsh UYT thema Braga-Neto, Ulisses. author. aut http://id.loc.gov/vocabulary/relators/aut 82006 Fundamentals of Pattern Recognition and Machine Learning [electronic resource] / by Ulisses Braga-Neto. 2nd ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XXI, 400 p. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Introduction -- Optimal Classification -- Sample-Based Classification -- Parametric Classification -- Nonparametric Classification -- Function-Approximation Classification -- Error Estimation for Classification -- Model Selection for Classification -- Dimensionality Reduction -- Clustering -- Regression -- Bayesian Machine Learning -- Scientific -- Machine Learning -- Appendices. This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks. Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter notebooks, which can be downloaded from the book website. Image processing Digital techniques. 64228 Computer vision. Machine learning. 55059 Pattern recognition systems. 65547 Bioinformatics. 64050 Computer Imaging, Vision, Pattern Recognition and Graphics. 65550 Machine Learning. 55059 Automated Pattern Recognition. 65551 Bioinformatics. 64050 Computer Vision. SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031609497 Printed edition: 9783031609510 Printed edition: 9783031609527 https://doi.org/10.1007/978-3-031-60950-3 ZDB-2-SCS ZDB-2-SXCS 62288 62288