Название: Developing Information Systems Accurately: A Wholistic Approach
Автор: Bert de Brock
Издательство: Springer
Год: 2023
Страниц: 265
Язык: английский
Формат: pdf (true)
Размер: 17.3 MB

This textbook shows how to develop the functional requirements of information systems. It emphasizes the importance to consider the complete development path of a functional requirement, i.e. not only the individual development steps but also their proper combination and their alignment. Even after decades of numerous bad experiences, many software development projects are still failing on at least one or even all three basic requirements for a project: - Too little (The project delivers inadequate functionality); - Too late (The project is not within time); - Too costly (The project is not within budget). Or, even worse, the project has been ended prematurely, usually after a lot of time and money have been spent, and without delivering any working functionality... The reasons for those failures usually lie at the very beginning: There is no clarity in what the customer really wants and needs, leading to incomplete and even wrong specifications, and subsequently programmers who fill in the functional gaps to the best of their own understanding. So, it is very important to get really clear what the customer wants and exactly needs and to make unambiguous, correct, and complete functional specifications. This book is written for (under)graduate students in software engineering or information systems who want to learn how to carry out adequate problem analysis, to make good system specifications, and/or to understand how to organize and manage an IS-development process.

Название: Software Engineering: Basic Principles and Best Practices
Автор: Sethi Ravi
Издательство: Cambridge University Press
Год: 2023
Страниц: 807
Язык: английский
Формат: pdf
Размер: 10.2 MB

Software engineering is as much about teamwork as it is about technology. This introductory textbook covers both. For courses featuring a team project, it offers tips and templates for aligning classroom concepts with the needs of the students' projects. Students will learn how software is developed in industry by adopting agile methods, discovering requirements, designing modular systems, selecting effective tests, and using metrics to track progress. The book also covers the 'why' behind the 'how-to', to prepare students for advances in industry practices. The chapters explore ways of eliciting what users really want, how clean architecture divides and conquers the inherent complexity of software systems, how test coverage is essential for detecting the inevitable defects in code, and much more. Ravi Sethi provides real-life case studies and examples to demonstrate practical applications of the concepts. Online resources include sample project materials for students, and lecture slides for instructors. This book is intended for a junior - or senior-level introductory course in software engineering. Students are expected to have enough programming maturity to engage in a team project.

Название: Mathematics of Deep Learning: An Introduction
Автор: Leonid Berlyand, Pierre-Emmanuel Jabin
Издательство: De Gruyter
Год: 2023
Страниц: 134
Язык: английский
Формат: pdf (true)
Размер: 10.8 MB

The goal of this book is to provide a mathematical perspective on some key elements of the so-called Deep Neural Networks (DNNs). Much of the interest in Deep Learning has focused on the implementation of DNN-based algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying mathematical ideas. We believe that a more foundational perspective will help to answer important questions that have only received empirical answers so far. Our goal is to introduce basic concepts from Deep Learning, e. g., mathematical definitions of DNNs, loss functions, the backpropagation algorithm, etc., in a rigorous mathematical fashion. We attempt to identify for each concept the simplest setting that minimizes technicalities but still contains the key mathematics.

Название: Machine Learning for Managers
Автор: Paul Geertsema
Издательство: Routledge
Год: 2023
Страниц: 181
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Machine Learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with Machine Learning (ML) are better placed to navigate the increasingly digital world we live in. There is a view that Machine Learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin Machine Learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what Machine Learning is about, but who lack a technical background in Computer Science, statistics or math. The book describes in plain language what Machine Learning is and how it works. In addition, it explains how to manage Machine Learning projects within an organization.

Название: AI-Based Metaheuristics for Information Security and Digital Media
Автор: Apoorva S. Shastri, Mangal Singh, Anand J. Kulkarni
Издательство: CRC Press
Серия: Advances in Metaheuristics
Год: 2024
Страниц: 151
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book examines the latest developments in Artificial Intelligence (AI)-based metaheuristics algorithms with applications in information security for digital media. It highlights the importance of several security parameters, their analysis, and validations for different practical applications. Drawing on multidisciplinary research including Computer Vision, Machine Learning, Artificial Intelligence, and modified/newly developed metaheuristics algorithms, it will enhance information security for society. It includes state-of-the-art research with illustrations and exercises throughout.

Название: Безопасность ASP. Net Core
Автор: Кристиан Венц
Издательство: ДМК Пресс
Год: 2023
Страниц: 388
Язык: русский
Формат: pdf
Размер: 31.4 MB

Приложения ASP.NET Core подвержены риску атак. Существуют конкретные меры, которые помогут избежать взлома. В книге показаны такие методы защиты веб-приложений ASP.NET Core, как безопасное взаимодействие с браузером, распознавание и предотвращение распространенных угроз, развертывание уникальных API безопасности этого фреймворка. Приводятся способы написания безопасного кода и примеры с аннотациями, а также полное описание встроенных инструментов безопасности ASP.NET Core. Рассматриваются реальные нарушения в системе безопасности, включая мошеннические расширения Firefox и кражу паролей в Adobe. Стек, который мы будем использовать в этой книге, – это .NET; а поскольку мы говорим о веб-приложениях, то в центре внимания будет фреймворк ASP.NET Core. Книга была написана с использованием .NET 6 и ASP.NET Core 6, но надеюсь, что она будет полезна и при работе с более новыми версиями.

Название: Python for Scientific Computing and Artificial Intelligence
Автор: Stephen Lynch
Издательство: CRC Press
Серия: The Python Series
Год: 2023
Страниц: 334
Язык: английский
Формат: pdf (true)
Размер: 27.7 MB

Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book has developed from a series of university, national and international workshops that I have been delivering for over twenty years. It is based on the programming language Python, which is a high-level programming language and supports functional, imperative, object-oriented and procedural styles of programming. Probably the most important aspect of Python is that it is open source and completely free to the user.

Название: Python The Complete Manual - 15th Edition, 2023
Автор: Jon White (Editor)
Издательство: Future Publishing
Год: 2023
Страниц: 132
Язык: английский
Формат: pdf (true)
Размер: 10,1 MB

Всегда хотели попробовать себя в программировании? Больше никаких отговорок, потому что Python - это идеальный способ начать! Python - отличный язык программирования как для новичков, так и для экспертов. Он разработан с учетом удобства чтения кода, что делает его отличным выбором для новичков, которые все еще привыкают к различным концепциям программирования. Язык популярен и имеет множество библиотек, что позволяет программистам добиться многого, используя относительно небольшой объем кода. На Python можно создавать самые разные приложения: можно использовать фреймворк Pygame для написания простых 2D-игр, можно использовать библиотеки GTK для создания оконного приложения, а можно попробовать что-то более амбициозное, например, создать приложение с использованием библиотек Python Bluetooth и Input для захвата ввода с USB-клавиатуры и передачи событий ввода на телефон Android.

Название: Training Data for Machine Learning: Human Supervision from Annotation to Data Science (8th Early release)
Автор: Anthony Sarkis
Издательство: O’Reilly Media, Inc.
Год: 2023-04-25
Страниц: 259
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

Your training data has as much to do with the success of your data project as the algorithms themselves--most failures in Deep Learning systems relate to training data. But while training data is the foundation for successful Machine Learning, there are few comprehensive resources to help you ace the process. This hands-on guide explains how to work with and scale training data. What is Training Data? Training Data is the control of a Supervised System. Training Data controls the system by defining the ground truth goals for the creation of Machine Learning models. This involves technical representations, people decisions, processes, tooling, system design, and a variety of new concepts specific to Training Data. In a sense, a Training Data mindset is a paradigm upon which a growing list of theories, research and standards are emerging. A Machine Learning (ML) Model that is created as the end result of a ML Training Process.

Название: Fast Python: High performance techniques for large datasets (Final Release)
Автор: Tiago Rodriques Antao
Издательство: Manning Publications
Год: 2023
Страниц: 304
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex Machine Learning applications. The purpose of this book is to help you write more efficient applications in the Python ecosystem. By more efficient, I mean that your code will use fewer CPU cycles, less storage space, and less network communication. The book takes a holistic approach to the problem of performance. We not only discuss code optimization techniques in pure Python, but we also consider the efficient use of widely used data libraries, like NumPy and Pandas. Because Python is not sufficiently performant in some cases, we also consider Cython when we need more speed. In line with this holistic approach, we also discuss the impact of hardware on code design: we analyze the impact of modern computer architectures on algorithm performance. We also examine the effect of network architectures on efficiency, and we explore the usage of GPU computing for fast data analysis. Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs.