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 English | 2022 | ISBN: 1801813574 | 443 pages | True PDF EPUB | 21.45 MB Learn the principles of quantum machine learning and how to apply them in finance. Purchase of the print or Kindle book includes a free eBook in the PDF format.  English | 2022 | ISBN: 168507930X | 268 pages | True PDF | 6.28 MB "Quantum field theory (QFT) is a theoretical framework that combines classical field theory, special relativity and quantum mechanics, and represents the forefront of theoretical physics. The four chapters of this book include new research on quantum field theory and present different perspectives on the subject. Chapter One applies the notion of clothing particles in QFT to the theory of nuclear forces and quantum electrodynamics. Chapter Two is based on results from black hole thermodynamics at all energy scales and demonstrates that there is a natural ultraviolet applicable boundary distant from the Planck scales in QFT. Chapter Three presents a version of quantum field theory based on discrete energy-momentum and illustrates this theory using examples of fermion and boson fields. Lastly, Chapter Four discusses in detail whether or not perturbative expansion series in quantum electrodynamics are convergent and points out that the disagreement between the experimental value of the muon g-2 and the theoretical one predicted in the standard model might be due either to the larger hadronic vacuum polarization contributions or to an unexpectedly large sum of the perturbative expansion series"-- [center]
 English | 2023 | ISBN: 9402421890 | 571 pages | True PDF EPUB | 33.38 MB This book is a translation of the 8th edition of Prof. Kazuhiko Nishijima's classical textbook on quantum field theory. It is based on the lectures the Author gave to students and researchers with diverse interests over several years in Japan. The book includes both the historical development of QFT and its practical use in theoretical and experimental particle physics, presented in a pedagogical and transparent way and, in several parts, in a unique and original manner. The Author, Academician Nishijima, is the inventor (independently from Murray Gell-Mann) of the third (besides the electric charge and isospin) quantum number in particle physics: strangeness. He is also most known for his works on several other theories describing particles such as electron and muon neutrinos, and his work on the so-called Gell-Mann–Nishijima formula.  English | 2022 | ISBN: 0128241535 | 393 pages | True PDF EPUB | 14.2 MB Quantum Dots: Fundamentals, Synthesis and Applications compiles key information, along with practical guidance on quantum dot synthesis and applications. Beginning with an introduction, Part One highlights such foundational knowledge as growth mechanisms, shape and composition, electrochemical properties, and production scale-up for quantum dots. Part Two goes on to provide practical guides to key chemical, physical and biological methods for the synthesis of quantum dots, with Part Three reviewing the application of quantum dots and a range of important use cases, including photocatalysis, energy cells and medical imaging. Drawing on the knowledge of its expert authors, this comprehensive book provides practical guidance for all those who already study, develop or use quantum dots in their work.  English | 2022 | ISBN: 978-1032406374 | 165 pages | True PDF | 6.04 MB Quantum Chemistry provides a coherent and structured approach in introducing the concept of 'quantum' to the students of quantum mechanics. An attempt is made to bring out the subtleties of quantum mechanics, hidden in its abstract laws and equations, applicable to the atomic domain by showing its relevance to the observable macroscopic world as well. The book will help students dispel the stigma associated with quantum mechanics. The emphasis on conceptual approach provides a platform to stand on, and a stimulus to pursue higher quantum mechanics―the doorway to the all-pervasive quantum world.  English | 2022 | ISBN: 978-3031046476 | 524 pages | True PDF EPUB | 56.72 MB Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses. To clearly connect theoretical concepts to practical implementations, the author provides many worked-out examples along with "Programming Tips" that encourage the reader to write quality Python code. The entire text, including all the figures and numerical results, is reproducible using the Python codes provided, thus enabling readers to follow along by experimenting with the same code on their own computers. Modern Python modules like Pandas, Sympy, Scikit-learn, Statsmodels, Scipy, Xarray, Tensorflow, and Keras are used to implement and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, interpretability, and regularization. Many abstract mathematical ideas, such as modes of convergence in probability, are explained and illustrated with concrete numerical examples. This book is suitable for anyone with undergraduate-level experience with probability, statistics, or machine learning and with rudimentary knowledge of Python programming.  English | 2023 | ISBN: 1032111038 | 458 pages | True EPUB | 7.13 MB This book focuses on the basics of Python programming fundamentals. It provides an introduction to present-day applications in technology and the upcoming state-of-art trends in a comprehensive manner. It is based on Python 3.x, and it covers the fundamentals of Python with object-oriented concepts having numerous worked out examples. This book also acts as a learning tool for students of beginner level as well as for researchers of advanced level. Each chapter contains numerous programming examples along with their outputs that explain the usage of the methods and functions discussed in the chapter. [center]  English | 2022 | ISBN: 978-1032111032 | 459 pages | True PDF | 36.34 MB The text focuses on the basics of Python programming fundamentals and introduction to present-day applications in technology and the upcoming state-of-art trends in a comprehensive manner. The text is based on Python 3.x and it covers the fundamentals of Python with object-oriented concepts having numerous worked-out examples. It provides a learning tool for the students of beginner level as well as for researchers of advanced level. Each chapter contains additional examples that explain the usage of methods/functions discussed in the chapter. It provides numerous programming examples along with their outputs. The book  English | 2022 | ISBN: 978-1683928232 | 323 pages | True PDF | 9.62 MB As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available. FEATURES:
 English | 2022 | ISBN: 1804611301 | 386 pages | True/Retail PDF EPUB | 17.14 MB Create end-to-end, reproducible feature engineering pipelines that can be deployed into production using open-source Python libraries Key Features |
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