Please use this identifier to cite or link to this item: http://dspace.univ-usto.dz/handle/123456789/648
Full metadata record
DC FieldValueLanguage
dc.contributor.authorOurdighi, Asmaa-
dc.date.accessioned2024-12-12T08:30:17Z-
dc.date.available2024-12-12T08:30:17Z-
dc.date.issued2024-12-12-
dc.identifier.urihttp://dspace.univ-usto.dz/handle/123456789/648-
dc.description.abstractNumerical analysis is fundamentally intertwined with computer science. The advent of high- performance computing has revolutionized the field, enabling the solution of complex mathematical problems that were previously intractable. Numerical methods are at the heart of computational software, from scientific simulations to data analysis tools. Computer scientists design efficient algorithms and data structures to implement these methods, while numerical analysts develop the mathematical foundations. This interdisciplinary collaboration has led to groundbreaking advancements in fields such as artificial intelligence, machine learning, and data science, where numerical techniques are essential for tasks like training neural networks, processing large datasets, and solving optimization problemsen_US
dc.subjectNumerical Analysis, Error Analysis, Linear Systemsen_US
dc.subjectDirect Methods, Gauss Method, LU Factorization, Iterative Methodsen_US
dc.subjectJacobi Method, Gauss-Seidel Method, Relaxation Methoden_US
dc.subjectLocalization of Eigenvalues, Gershgorin Circle Theorem, Power Method.en_US
dc.titleNumerical Methods Courseen_US
dc.typeOtheren_US
Appears in Collections:Cours en ligne

Files in This Item:
File Description SizeFormat 
NMC_AO.pdf1,68 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.