|
 |
|
 |
|
|
 |
|  |
|
 Название: Generative AI: Phishing And Cybersecurity Metrics
Автор: Ravindra Das
Издательство: CRC Press
Год: 2025
Страниц: 177
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
The cybersecurity landscape is changing, for sure. For example, one of the oldest threat variants is that of phishing. It evolved in the early 1990s, but even today it is still being used as a primary threat variant and has now become much more sophisticated, covert, and stealthy in nature. For example, it can be used to launch ransomware, social engineering, and extortion attacks. The advent of Generative AI is making this much worse. For example, a cyberattacker can now use something like ChatGPT to craft the content for phishing emails that are so convincing that it is almost impossible to tell the difference between what is real and what is fake. This is also clearly evident in the use of deepfakes, where fake images of real people are replicated to create videos to lure unsuspecting victims to a fake website. But Generative AI can also be used for the good to combat Phishing Attacks. This is the topic of this book. In this, we cover the following: --A review of phishing; - A review of AI, Neural Networks, and Machine Learning; - A review of Natural Language Processing, Generative AI, and the Digital Person; - A proposed solution as to how Generative AI can combat phishing attacks as they relate to Privileged Access accounts. | |
Разместил: Ingvar16 23-07-2024, 22:45 | Комментарии: 0 | Подробнее
| | | |
 |
|  |
|
|
|
|
|
|
| |
|
 Название: Effectively Learning to Code: A Brain-Based Approach
Автор: Eric Wise
Издательство: Skill Foundry
Год: 2024
Страниц: 203
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
Unlock your coding potential with brain-based learning strategies! This book has provided a lot of information that you can use to build a robust toolkit designed to elevate your coding prowess through cognitive science principles, practical strategies, and personalized learning techniques. The holistic approach adopted here ensures that you’re not just mechanically following instructions but are truly comprehending and retaining what you learn, thereby enabling deeper and more effective coding practices. This book is designed to address your unique challenges and provide practical, brain-based strategies to enhance your learning and coding proficiency. This book is your companion in the journey to mastering coding. With its unique blend of brain-based learning strategies, practical advice, and real-world examples, it’s designed to address your challenges and guide you toward success. Whether you’re just starting or looking to enhance your skills, the insights and methods you’ll find here are tailored to meet your needs and help you overcome obstacles. Now is the time to transform your approach to learning coding. Embrace the techniques, implement the strategies, and watch your progress soar. Imagine the satisfaction of solving complex problems, creating innovative projects, and feeling confident in your coding abilities. This book is more than just a guide; it’s a catalyst for your growth and success. Transform your approach to coding education and accelerate your path to becoming a skilled programmer. Are you ready to rewire your brain for coding success? | |
Разместил: Ingvar16 23-07-2024, 14:56 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 23-07-2024, 11:32 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 23-07-2024, 09:47 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 23-07-2024, 05:40 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 23-07-2024, 05:23 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 22-07-2024, 20:47 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
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.
| |
Разместил: Chipa 22-07-2024, 16:04 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
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.
| |
Разместил: Chipa 22-07-2024, 14:10 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
|
|
|
|
|
| |
|
 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. | |
Разместил: Ingvar16 22-07-2024, 02:56 | Комментарии: 0 | Подробнее
| | | |
|
| |
|
Навигация
Вход на сайт
Реклама
