Название: Introduction to Multidisciplinary Science with Artificial Intelligence: Geodesy, Geotherms, Quantum Entanglement, and Spectroscopy
Автор: Luc Thomas Ikelle
Издательство: CRC Press
Год: 2024
Страниц: 823
Язык: английский
Формат: pdf (true)
Размер: 50.9 MB

With the huge progress being made in the field of Artificial Intelligence (AI), the new jobs are about innovation. Broadly speaking, AI is a set of techniques that are aimed at approximating some aspects of human or animal cognition by inserting computer software into robots and other related systems. AI systems can nowadays perform many traditionally human tasks with high efficiency and without errors. The book is about multidisciplinary science education. The challenges of our time, such as improving the length and quality of lives on Earth and short- and long-distance communication and transportation. In this book, we provide readers with the multidisciplinary education necessary to meet the scientific and technological challenges of our time while optimizing the college experience for students. The fundamental notions addressed in this book include gravitational forces and energy; dark matter and dark energy; heat transfer in solid Earth, stars’ interiors, and human bodies; electromagnetic radiation and spectroscopy; quantum entanglement and computing; accretion disks; matter in plasma state; and exoplanets. We illustrate the importance of these notions with applications across disciplines, including monitoring the deformation of the solid Earth’s surface using satellite measurements, unusual gravity anomalies in Antarctica, a view and characterization of the far side of our Moon, Earth’s climate, Titan’s anti-greenhouse effect, long-distance communication between Earth and the planets and exoplanets, etc. Finally, the book contains analytical and computational problems, including MATLAB software developed especially for the classes associated with this book.

Название: Financial Data Analytics with R: Monte-Carlo Validation
Автор: Jenny K. Chen
Издательство: CRC Press
Год: 2025
Страниц: 298
Язык: английский
Формат: pdf (true)
Размер: 13.7 MB

Financial Data Analysis with R: Monte-Carlo Validation is a comprehensive exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through practical explanations and examples, enabling them to develop a solid foundation of these methods in R and their applications in finance. This book aims to serve as a comprehensive guide for students, researchers, and practitioners seeking to harness the power of R for analyzing financial data. The journey begins with a solid foundation in both financial theory and R programming, gradually progressing to more advanced topics such as time series analysis, risk and risk management. The practical examples provided throughout the book are rooted in real-world financial scenarios, offering readers a bridge between academic concepts and practical applications. The book goes beyond just teaching statistical methods in R and incorporates a unique section of informative Monte-Carlo simulations. These Monte-Carlo simulations are uniquely designed to showcase the reader the potential consequences and misleading conclusions that can arise when fundamental model assumptions are violated. Through step-by-step tutorials and realworld cases, readers will learn how and why model assumptions are important to follow. With a focus on practicality, Financial Data Analysis with R: Monte-Carlo Validation equips readers with the skills to construct and validate financial models using R.

Название: Linear Algebra in Data Science
Автор: Peter Zizler, Roberta La Haye
Издательство: Birkhäuser/Springer
Год: 2024
Страниц: 202
Язык: английский
Формат: pdf (true), epub
Размер: 16.3 MB

Data Science is an exciting, emerging research area in the forthcoming digital age. It draws from a multitude of disciplines. We intend to show the reader the fundamental role of linear algebra in Data Science. This book showcases various Data Science topics as seen through the lens of linear algebra. This textbook explores applications of linear algebra in Data Science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science is suitable as a supplement to a standard linear algebra course. We assume the reader is either familiar with foundational results in linear algebra or willing to consult a linear algebra text of their choice for specific results as they read our text. Readers with the basic linear algebra knowledge and who are interested in Data Science courses will find our text useful. Linear algebra is a pillar for Data Science, and understanding this will enable the student to grasp the procedures and techniques used. It will also provide the student with the ability to go further into the Data Science paradigm.

Название: Artificial Intelligence: What Is Behind the Technology of the Future?
Автор: Gerhard Paaß, Dirk Hecker
Издательство: Springer
Год: 2024
Страниц: 485
Язык: английский
Формат: pdf (true)
Размер: 33.9 MB

Artificial Intelligence (AI) is already present in our daily routines, and in the future, we will encounter it in almost every aspect of life – from analyzing X-rays for medical diagnosis, driving autonomous cars, maintaining complex machinery, to drafting essays on environmental problems and drawing imaginative pictures. The potentials of AI are enormous, while at the same time many myths, uncertainties and challenges circulate that need to be tackled. This book is addressed to the general public, from interested citizens to corporate executives who want to develop a better and deeper understanding of AI technologies and assess their consequences. Mathematical basics, terminology, and methods are explained in understandable language. Adaptations to different media such as images, text, and speech and the corresponding generative models are introduced. A concluding discussion of opportunities and challenges helps readers evaluate new developments, demystify them, and assess their relevance for the future. The purpose of this book is to clearly demonstrate the new possibilities of Machine Learning in different application areas, such as autonomous driving, medical diagnosis or the analysis of the meaning of language. It turns out that the methods used are composed of very simple operations, such as addition and multiplication. These gain their performance by being applied to very large sets of numbers and several times in succession. If one would like to understand the technical Chaps. 3, 4, 5, 6, 7, 8, and 9 in detail, a mathematical understanding at senior high school level is sufficient.

Название: C++ & Python & Tricks and Tips - 18th Edition 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 28.9 MB

Книга "C++ & Python & Tricks and Tips" - это первый и единственный выбор для начинающих, чтобы узнать все, что им нужно знать о кодировании и программировании. Написанное простым английским языком, это отдельное руководство содержит множество полезных советов и пошаговых иллюстрированных уроков. С помощью этого совершенно нового руководства вы узнаете все необходимое для создания собственных интересных приложений. С этим неформальным руководством у вас никогда не возникнет нерешенных проблем или вопросов по мере изучения, освоения и совершенствования навыков программирования на C++ и Python.

Название: Probability and Statistics for Machine Learning: A Textbook
Автор: Charu C. Aggarwal
Издательство: Springer
Год: 2024
Страниц: 530
Язык: английский
Формат: pdf (true), epub
Размер: 41.5 MB

This book covers probability and statistics from the Machine Learning perspective. Most of Machine Learning is directly or indirectly related to probability and statistics. After all, Machine Learning is all about making predictions based on data, which inevitably leads to statistical methods. These statistical methods are often couched as models, which use probabilities to quantify the likelihoods of events. Therefore, having a strong background in probability and statistics is critical. The familiarity required with probability and statistics often goes well beyond what is taught in undergraduate curricula. As a result, this presents a challenge to beginners in the field. In many cases, the type of techniques required from probability and statistics are specific to Machine Learning, which is not covered by generic courses on probability and statistics. This book therefore develops a treatment of probability and statistics from the specific perspective of Machine Learning. This book teaches probability and statistics with a specific focus on Machine Learning applications. As a natural consequence of this approach, many key concepts in Machine Learning are covered in detail. Therefore, it is possible to learn a significant amount of Machine Learning while learning probability and statistics from this book. The book contains over 200 worked examples in order to elucidate key concepts.

Название: CUDA Fortran для инженеров и научных работников: Рекомендации по эффективному программированию
Автор: Рутш Г., Фатика М.
Издательство: Москва
Год: 2014
Cтраниц: 364
Формат: pdf (ocr)
Размер: 41 мб
Язык: русский

Fortran – один из важнейших языков программирования для высокопроизводительных вычислений, для которого было разработано множество популярных пакетов программ для решения вычислительных задач.

Название: Explainable AI (XAI) for Sustainable Development: Trends and Applications
Автор: Lakshmi D, Ravi Shekhar Tiwari, Rajesh Kumar Dhanaraj
Издательство: CRC Press
Год: 2024
Страниц: 335
Язык: английский
Формат: pdf (true)
Размер: 20.9 MB

This book presents innovative research works to automate, innovate, design, and deploy Artificial Intelligence (AI) for Real-World Applications. It discussed AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with Machine Learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. Artificial Intelligence has rapidly permeated our lives, transforming industries, healthcare, and our interactions with technology. While AI promises innovation and efficiency, its opacity and complexity raise concerns about trust, accountability, and ethical implications. To address these challenges, Explainable AI (XAI) emerged, bridging the gap between Machine Learning and human understanding. XAI seeks to explain how AI systems make decisions, ensure their trustworthiness, and evaluate their societal and ethical impact. This book provides a multifaceted realm of XAI, covering its theoretical foundations, practical applications, and ethical considerations. Through expert insights, real‑world examples, and accessible explanations, we demystify XAI’s complexities for a wide audience. Along the way, we explore the black box of AI models, learn various interpretation techniques, and examine responsible AI development and deployment.

Название: .NET in Action, 2nd Edition
Автор: Dustin Metzgar
Издательство: Manning Publications
Год: 2024
Страниц: 360
Язык: английский
Формат: pdf (true)
Размер: 24.7 MB

Learn to build standout line-of-business applications using Microsoft’s .NET Framework, the premier platform for enterprise business development. .NET in Action, Second Edition offers a clear-headed introduction to implementing full-featured, cross-platform professional applications on the Microsoft .NET platform. It’s written by Dustin Metzgar, an industry veteran who helped develop both the original .NET Framework and .NET Core. Based on the bestselling .NET Core in Action, this new edition has been completely rewritten and updated to .NET 7. Using Microsoft’s powerful .NET platform, you can build web and desktop applications for almost any operating system or device. .NET powers everything from lightweight web apps to industrial-strength distributed systems. Designed to be cross-platform and ready for hybrid cloud deployments, it’s perfect for deploying servers and services almost anywhere. It’s even a great place to start with game development and machine learning! With so many options, it’s important to have the big picture perspective this book provides. For developers who know the basics of object-oriented programming. Examples in C#.

Название: ЕШКО. Программирование на Python для начинающих
Автор: Коллектив
Издательство: ЕШКО
Год: 2024
Формат: PDF
Страниц: много
Размер: 19 Mb
Язык: Русский

Решили освоить язык Python, но не знаете, с чего начать? Тогда Вам подойдет наш курс «Программирование на Python для начинающих». Для обучения не потребуются ни специальные знания, ни техническое образование. Погружение в язык программирования «Питон» будет несложным и последовательным: от базовых основ до тонкостей разработки и оптимизации кода.