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Advanced Computing Techniques for Optimization in Cloud
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Название: Advanced Computing Techniques for Optimization in Cloud
Автор: H S Madhusudhan, Punit Gupta, Pradeep Singh Rawat
Издательство: CRC Press
Год: 2025
Страниц: 263
Язык: английский
Формат: pdf (true)
Размер: 22.1 MB

This book focuses on the current trends in research and analysis of virtual machine placement in a cloud data center. It discusses the integration of Machine Learning models and metaheuristic approaches for placement techniques. Taking into consideration the challenges of energy-efficient resource management in cloud data centers, it emphasizes upon computing resources being suitably utilised to serve application workloads in order to reduce energy utilisation, while maintaining apt performance. This book provides information on fault-tolerant mechanisms in the cloud and provides an outlook on task scheduling techniques. Nature-inspired algorithms offer versatile solutions to key challenges in cloud computing. Workload prediction and optimization benefit from algorithms like genetic algorithms (GAs), particle swarm optimization, and ant colony optimization, which replicate natural selection, swarm behavior, and collective intelligence. These algorithms analyze historical patterns and forecast future demand shifts, enabling resource allocation adjustments that prevent inefficiencies. They also contribute to fair multi-tenant environments by drawing on predator–prey dynamics to distribute resources equitably. Cost optimization thrives through algorithms like simulated annealing, mirroring cooling metal’s energy reduction process to finely balance performance and cost. These algorithms also fortify security and compliance, with immune system-inspired mechanisms enhancing resource isolation and data protection. Kubernetes, an open-source container orchestration platform, serves as a prime example of achieving interoperability between different cloud platforms. Kubernetes’ standardized APIs and portable manifest files, describing application configurations, enable effortless migration. The platform’s inherent load balancing, scaling, and auto-recovery capabilities ensure consistent behavior, regardless of the underlying cloud infrastructure. The text is for postgraduate students, professionals, and academic researchers working in the fields of Computer Science and information technology.


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Research Advances in Intelligent Computing: Volume 2
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Название: Research Advances in Intelligent Computing: Volume 2
Автор: Anshul Verma, Pradeepika Verma
Издательство: CRC Press
Год: 2025
Страниц: 261
Язык: английский
Формат: pdf (true)
Размер: 13.9 MB

Researchers and scientists have invested a great deal of effort into developing computers and other devices to be more capable of doing a wider range of tasks. As a result, the potential of computers to do a wide range of tasks in different environments, at varying speeds, and in smaller forms is growing dramatically every day. Currently, there is a race to create robots or computers with human-level intelligence. Artificial Intelligence (AI) is the ability of a machine or software to think like a human being. The study of the human brain, specifically how humans learn, make decisions, and react when trying to solve issues, is the basis of AI. The creation of intelligent software and systems, or Intelligent Computing (IC), is the outcome of AI studies. An IC system can perceive, reason, learn, and use language. In IC systems, AI and other cutting-edge techniques are employed to create system intelligence. IC has been applied to almost every area of Computer Science, including networking, software engineering, gaming, robotics, expert systems, natural language processing (NLP), computer vision, image processing, and Data Science. Today, IC is also used to resolve a variety of complicated problems in many different fields, including disease prediction in medicine, crop productivity prediction in agriculture science, market growth prediction in economics, weather forecasting, etc. For all of these reasons, this book provides the most recent developments in AI as well as IC. In this perspective, the book contains the most recent research on Machine Learning, neural networks, Deep Learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and other related topics.


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Python Programming for Economics and Finance (Updated)
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Название: Python Programming for Economics and Finance (Updated)
Автор: Thomas J. Sargent, John Stachurski
Издательство: QuantEcon
Год: Jun 12, 2024
Страниц: 382
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book presents a set of lectures on Python programming for economics and finance. This is the first text in the series, which focuses on programming in Python. Python has experienced rapid adoption in the last decade and is now one of the most popular programming languages. Python is a general-purpose language used in almost all application domains such as: • communications; • web development; • CGI and graphical user interfaces; • game development; • resource planning; • multimedia, data science, security, etc., etc., etc. Meanwhile, Python is also very beginner-friendly and is found to be suitable for students learning programming and recommended to introduce computational methods to students in fields other than Computer Science. Python is also replacing familiar tools like Excel as an essential skill in the fields of finance and banking. One nice feature of Python is its elegant syntax — we’ll see many examples later on. Elegant code might sound superfluous but in fact it’s highly beneficial because it makes the syntax easy to read and easy to remember. Remembering how to read from files, sort dictionaries and other such routine tasks means that you don’t need to break your flow in order to hunt down correct syntax. Closely related to elegant syntax is an elegant design. Features like iterators, generators, decorators and list comprehensions make Python highly expressive, allowing you to get more done with less code. Namespaces improve productivity by cutting down on bugs and syntax errors.


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Applications of AI for Interdisciplinary Research
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Название: Applications of AI for Interdisciplinary Research
Автор: Sukhpal Singh Gill
Издательство: CRC Press
Год: 2025
Страниц: 313
Язык: английский
Формат: pdf (true)
Размер: 12.6 MB

Applying Artificial Intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields. The proliferation and successful deployment of AI algorithms are fuelling these changes, which can be seen in fields as disparate as healthcare and emerging Internet of Things (IoT) applications. Machine learning techniques, and AI more broadly, are expected to play an ever-increasing role in the modelling, simulation, and analysis of data from a wide range of fields by the interdisciplinary research community. Ideas and techniques from multidisciplinary research are being utilised to enhance AI; hence, the connection between the two fields is a two-way street at a crossroads. Algorithms for inference, sampling, and optimisation, as well as investigations into the efficacy of Deep Learning, frequently make use of methods and concepts from other fields of study. Cloud computing platforms may be used to develop and deploy several AI models with high computational power. The intersection between multiple fields, including math, science, and healthcare, is where the most significant theoretical and methodological problems of AI may be found. To gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of Machine Learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic.


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Compilers: Principles, Techniques, and Tools, Updated 2nd Edition
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Название: Compilers: Principles, Techniques, and Tools, Updated 2nd Edition
Автор: Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffrey D. Ullman
Издательство: Pearson
Год: 2023
Страниц: 1354
Язык: английский
Формат: epub
Размер: 15.3 MB

Pearson’s flagship title Compilers: Principles, Techniques and Tools, known to professors, students, and developers worldwide as the "Dragon Book," is available in a new edition to reflect the current state of compilation. This book provides the foundation for understanding the theory and practice of compilers. Revised and updated with new chapters on Programming Language Semantics and Undefined Behaviour Semantics, the title addresses modern issues in compiler design. However, the authors, recognizing that few readers will ever go on to construct a compiler, retain their focus on the broader set of problems faced in software design and software development. The reader should possess some “computer-science sophistication,” including at least a second course on programming, and courses in data structures and discrete mathematics. Knowledge of several different programming languages is useful.


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Thank Go! Многозадачность в Golang
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Название: Thank Go! Многозадачность в Golang
Автор: Антон Жиянов
Издательство: Stepik
Год: 2023
Формат: PDF
Страниц: много
Размер: 18 Mb
Язык: Русский

Курс рассчитан на программистов, которые уже знают основы Golang: от базовых конструкций языка до интерфейсов и ошибок. Горутины и каналы при этом можно не знать — мы рассмотрим инструменты многозадачности с нуля.


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Obsidian.md. Крепкий фундамент системы заметок
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Название: Obsidian.md. Крепкий фундамент системы заметок
Автор: Антон Дворкин
Издательство: Stepik
Год: 2024
Формат: HTML
Страниц: много
Размер: 38 Mb
Язык: Русский

Obsidian - отличный инструмент для ведения заметок, сохранения и последующего поиска полезной и справочной информации, работы с задачами, творчества и других целей. В рамках обучающей программы вы изучите Obsidian так, чтобы смочь быстро начать в нем работать, и делать это стабильно и эффективно. Но не только - также вы освоите фундамент работы с персональными базами знаний, который сможете применить в разных приложениях.



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Deep Learning for Finance: Creating Machine and Deep Learning Models for Trading in Python
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Название: Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python
Автор: Sofien Kaabar
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 362
Язык: английский
Формат: pdf (true), epub (true)
Размер: 16.0 MB

Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on Machine Learning and reinforcement learning. Sofien Kaabar—financial author, trading consultant, and institutional market strategist—introduces Deep Learning strategies that combine technical and quantitative analyses. By fusing Deep Learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Deep Learning is a slightly more complex and more detailed field than Machine Learning. Machine Learning and Deep Learning both fall under the umbrella of Data Science. As you will see, Deep Learning is mostly about neural networks, a highly sophisticated and powerful algorithm that has enjoyed a lot of coverage and hype, and for good reason: it is very powerful and able to catch highly complex nonlinear relationships between different variables. The book assumes you have basic background knowledge in both Python programming (professional Python users will find the code very straightforward) and financial trading. I take a clear and simple approach that focuses on the key concepts so that you understand the purpose of every idea.


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Excel with AI: A Comprehensive Guide to CoPilot and Python Integration
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Название: Excel with AI: A Comprehensive Guide to CoPilot and Python Integration
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 664
Язык: английский
Формат: pdf, epub, azw3, mobi
Размер: 10.1 MB

Unlock the Ultimate Power of Excel with AI at Your Fingertips. Dive into the depths of advanced Excel techniques with "Excel with AI", the definitive guide for enthusiasts eager to harness the full potential of Excel through Artificial Intelligence (AI) and programming. Tailored for those who have mastered the basics and are now ready to explore uncharted territories, this book goes beyond the fundamentals to reveal sophisticated methods that will revolutionize your data analysis and automation skills. Discover how to seamlessly integrate Python within Excel using the groundbreaking Py function, unleashing new possibilities for data manipulation, visualization, and analysis. Learn to collaborate effortlessly with AI-powered COPILOT, enhancing your productivity and efficiency. Explore the harmonious synergy between Python and Excel, crafting dynamic solutions that were once unimaginable. And for those who relish the control and flexibility of VBA, delve into advanced scripting techniques to automate complex tasks with precision. Whether you’re a data scientist, analyst, or developer, "Excel with AI" is your comprehensive resource for staying ahead in a world where Excel and AI converge. Packed with real-world examples, step-by-step tutorials, and expert insights, this book ensures you not only understand the concepts but also apply them to solve practical problems.


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Learning C# Through Small Projects
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Название: Learning C# Through Small Projects
Автор: Denis Panjuta, Jafar Jabbarzadeh
Издательство: Springer
Год: 2024
Страниц: 398
Язык: английский
Формат: pdf (true)
Размер: 22.9 MB

In the ever-evolving world of software development, the ability to adapt, learn, and innovate is paramount. C# has emerged as a versatile and powerful language, enabling developers to craft everything from enterprise applications to captivating games. However, the journey to mastering C# can be daunting, especially when faced with dense textbooks and abstract concepts. Learning C# by Small Projects seeks to bridge this gap, offering a hands-on approach to understanding advanced C# concepts through engaging projects and minigames. The rationale behind this book is simple: learning by doing. Instead of wading through pages of theory, you’ll be diving straight into the action, building 11 distinct projects that range from an interactive storytelling program to a responsive Discord chatbot. Each project is meticulously designed to introduce and reinforce specific C# concepts, ensuring that you not only understand the theory but can also apply it in real-world scenarios. The book is structured to provide a gradual learning curve. The initial chapters lay the foundation, introducing you to the basics of C# programming. As you progress, the projects become more intricate, delving into advanced topics such as asynchronous operations, data integrity, and API integration. By the end of the book, you'll have a comprehensive understanding of C# and a portfolio of projects to showcase your skills.


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