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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Fundamental Mathematical Concepts for Machine Learning in Science
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Fundamental Mathematical Concepts for Machine Learning in Science
Umberto Michelucci (Broschiert, Englisch)
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Beschreibung
This book is for individuals with a scientific background who aspire to apply machine learning within various natural science disciplines—such as physics, chemistry, biology, medicine, psychology and many more. It elucidates core mathematical concepts in an accessible and straightforward manner, maintaining rigorous mathematical integrity. For readers more versed in mathematics, the book includes… advanced sections that are not prerequisites for the initial reading. It ensures concepts are clearly defined and theorems are proven where it's pertinent. Machine learning transcends the mere implementation and training of algorithms; it encompasses the broader challenges of constructing robust datasets, model validation, addressing imbalanced datasets, and fine-tuning hyperparameters. These topics are thoroughly examined within the text, along with the theoretical foundations underlying these methods. Rather than concentrating on particular algorithms this book focuses on the comprehensive concepts and theories essential for their application. It stands as an indispensable resource for any scientist keen on integrating machine learning effectively into their research. Numerous texts delve into the technical execution of machine learning algorithms, often overlooking the foundational concepts vital for fully grasping these methods. This leads to a gap in using these algorithms effectively across diverse disciplines. For instance, a firm grasp of calculus is imperative to comprehend the training processes of algorithms and neural networks, while linear algebra is essential for the application and efficient training of various algorithms, including neural networks. Absent a solid mathematical base, machine learning applications may be, at best, cursory, or at worst, fundamentally flawed. This book lays the foundation for a comprehensive understanding of machine learning algorithms and approaches. 58,84 €
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Technische Daten
Erscheinungsdatum
17.05.2025
Sprache
Englisch
EAN
9783031564338
Herausgeber
Springer International Publishing
Sonderedition
Nein
Autor
Umberto Michelucci
Seitenanzahl
249
Einbandart
Broschiert
Schlagwörter
Machine Learning, Mathematics, Model Validation, Sampling Theory, Hyper-parameter Tuning, Linear Algebra
Thema-Inhalt
UYQM - Maschinelles Lernen
PSAX - DV-gestützte Biologie/Bioinformatik
PHU - Mathematische Physik
T - Technologie, Ingenieurswissenschaft, Landwirtschaft, Industrieprozesse
UYQ - Künstliche Intelligenz
Höhe
235 mm
Breite
15.5 cm
Transparenz & Sicherheit
Hersteller: Palgrave Macmillan, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com, Springer Nature Customer Service Center GmbH
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