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Название: Taming Your Dragon: Addressing Your Technical Debt
Автор: Andrew Richard Brown
Издательство: Apress
Год: 2024
Страниц: 372
Язык: английский
Формат: pdf
Размер: 10.1 MB

Technical debt is an often-overlooked problem that the software industry needs to take more seriously. All organizations are impacted by it, most wish that they had less of it, but need help in understanding the nature of the beast. This book aims to clear up any misconceptions and show you how to implement a sound technical debt management program to suit your company’s needs. You’ll learn the greatest challenge in solving the technical debt dilemma is not to find solutions to it, but rather to find solutions to the human and organizational issues that lead to that debt. For example, convincing senior stakeholders of the importance of addressing technical debt, getting stakeholders to acknowledge how their actions lead to unintentional debt, and enabling teams to prioritize technical debt over short-term goals. Therefore, this book is divided into three parts: defining technical debt, understanding technical debt, and tackling technical debt. It begins by explaining why technical debt should not be considered a technical problem, but rather a problem of how trade-off decisions are made. You’ll then examine how making decisions using the affect heuristic, more commonly known as a “gut feeling,” can lead to unnecessary technical debt, followed by some techniques for combating your vulnerability to this trap. This book is aimed at people in software teams, both those on projects, who are sometimes making decisions that result in technical debt, as well as those in support of DevOps, who must deal with the consequences of that debt. However, the book is not intended to be used to address that debt directly. Such an approach will not lead to any lasting change. Instead, this book will help you understand technical debt’s underlying causes and then enable you to advocate to stakeholders how you can address those causes in a planned intervention aimed at producing lasting improvement. This book is also aimed at managers and business stakeholders, who wish to understand why software development takes so long and costs so much.

Название: Understanding Fourier Transforms with Python: A Practical Approach
Автор: Hayden Van Der Post
Издательство: Reactive Publishing
Год: 2024
Страниц: 576
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

Unlock the power of one of the most essential tools in signal processing and data analysis with "Understanding Fourier Transforms with Python: A Practical Approach". This indispensable guide dives beyond the basics, welcoming enthusiasts and professionals eager to expand their knowledge and apply sophisticated techniques to their projects. Building on the foundations laid by top-selling introductory texts, this book delves into advanced concepts and practical applications of Fourier transforms using Python, the increasingly popular language of scientific computing. With clear explanations, hands-on examples, and practical insights, you'll discover how to harness the full potential of Fourier analysis to solve complex problems in various domains, from engineering and physics to Data Science and beyond. Whether you're a seasoned professional or an eager learner striving to deepen your understanding of Fourier transforms, this book equips you with the practical knowledge and skills needed to succeed. Embrace the journey of mastery with "Understanding Fourier Transforms with Python: A Practical Approach", and unlock new dimensions of analysis and creativity.

Название: Quant Developers' Tools and Techniques in Python: Volume 1: Statistics, Visualization, Pandas DataFrame, Simple- & Multiple Linear Regression
Автор: Manfred Hindering
Издательство: Quant Books
Серия: Quant Developers' Tools and Techniques
Год: 2024
Страниц: 860
Язык: английский
Формат: epub
Размер: 16.3 MB

As a quant developer in the past, it was quite challenging to acquire suitable datasets for any meaningful quantitative analysis. As technological innovations such as decentralized trading platforms occur, more programming savvy traders enter the scene and actively attempting to conquer and master this innovative field. This is in particular true for the crypto markets, where the trading platforms are built with the programmer in mind, therefore it has never been easier to retrieve market data and process it in an automated fashion. As a programmer, times have never been better to make a living by trading and coding - either individually or for trading firms around the world. Technological advances in computing equipment, programming and analytical tools allows the keen programmer to “make a killing” while doing something you enjoy doing. The crypto market, for example, represents an asset class - much like the forex market. However, it is still young and presents its fair share of inefficiencies and idiosyncrasies, which translate into opportunities for the astute quant developer to exploit. This volume introduces the tools and techniques for the programming-oriented developer to take advantages of such opportunities in an automated fashion. The bad news is, in order to succeed in this ever evolving and challenging field, you will have to know a lot of mathematics, statistics, coding, financial & market theory, and so on.

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.

Название: Основы языка программирования 1С 8.3
Автор(ы): Дадян Э.Г.
Издательство: Вузовский учебник
Год: 2020
Страниц: 134
Формат: PDF
Размер: Мб
Язык: русский

Основы языка программирования 1С 8.3, представленные в данном учебном пособии, предназначены и для начинающих, и для продвинутых пользователей. Изложение материала в учебном пособии разбито на два раздела. В первом разделе даются основы языка программирования 1С 8.3 для начинающих. Во втором разделе применение языка 1С 8.3 дается для продвинутых пользователей — в справочной форме, на конкретных примерах.

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?

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.

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.

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.

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.