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This book is intended to provide a self-contained introduction to the principles of Quantum Mechanics, based on the analysis of measurement processes of microscopic systems and the introduction of the physical observables as generators of symmetry transformations. After standard training arguments the applications are mainly focused on atomic and nuclear phenomena, as they occur on a quite different space-time scale. Thus, the text flows from the simplest systems, i.e. proton-electron in the hydrogen atom and proton-neutron in the Deuteron nucleus, to the complex many- body systems, i.e. stable states of atoms and nuclei of the periodic table, and finally to infinite many-body systems, including atomic and nuclear fluids. A digression is made on the application to astrophysical compact systems. The textbook is suitable for upper undergraduate students and graduate students in physics and related majors.
Additional questions and answers via app: Download the Springer Nature Flashcards app free of charge and use exclusive additional material to test your knowledge.
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This book covers all aspects of machine learning (ML) from concepts and math to ML programming. ML concepts and the math associated with ML are written from an application perspective, rather than from a theoretical perspective. The book presents concepts and algorithms precisely as they are used in real-world applications, ensuring a seamless and practical understanding with no gap between theory and practice.
In a distinctive approach, the book''s content is complemented by video lectures whose details can be found inside the book. This innovative approach offers readers a multimedia learning experience, accommodating different learning preferences, and reinforcing the material through visual and auditory means. If you are new to Artificial Intelligence and Machine Learning, this could be the first book you read and the first video course you take.
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Nature of Variation in Tone Sandhi Patterns of Shanghai and Wuxi Wu
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Nature Inspired Computing
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Harmony Search and Nature Inspired Optimization Algorithms
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