Название: An Introduction to the Management of Complex Software Projects
Автор: Veljko Milutinović, Filip Đorđević, Miloš Kotlar, Jakob Salom
Издательство: Cambridge Scholars Publishing
Год: 2024
Страниц: 246
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book explores the challenges of managing software projects, such as changing requirements, uncertain technologies, and evolving user needs, provides strategies for addressing these and other emerging issues, and contains a number of eye-opening perspectives from experts in different fields. Instead of relying solely on traditional project management techniques, the book presents a holistic, adaptive, and flexible framework that takes into account the unique challenges of each particular case of software development. It recognizes that software development is a complex and creative process that involves people with diverse skills and personalities, and provides insights into how to motivate and manage teams, how to communicate effectively, how to automate processes, and how to deal with conflict and uncertainty, from computer engineering and mathematical logic, all the way to advanced geophysics and earthquake engineering. It provides a wealth of practical advice and guidance, as well as insights into the latest schools of thought related to software project management. This section is based on the practical implementation of the software solutions carried out in a Python environment with Keras and TensorFlow, as well as in the Matlab framework. The presented programming codes, based mainly on Artificial Neural Networks (ANNs) were formed for regression issues intended for predictive analyses, but the fundamentals can also be applied to classification problems with appropriate model adaptation. In addition, per the author’s selection, the basics for the application of some mentioned alternative techniques that are widely used in the construction industry such as Deep-Learning, Random Forest or Support Vector Machines are given, with detailed step-by-step instructions for building a full model with all phases of data processing and extraction of the results, applicable to a wide range of engineering tasks.

Название: Software Design
Автор: Bechoo Lal
Издательство: Toronto Academic Press
Год: 2024
Страниц: 239
Язык: английский
Формат: pdf (true)
Размер: 37.0 MB

This book is a comprehensive guide to the principles and practices of designing software systems. It covers topics such as software architecture, design patterns, object-oriented design, and software development methodologies. The book is intended for software developers, architects, and project managers who want to learn how to design effective software systems. By following the guidelines provided in this book, readers can create software that is maintainable, scalable, and adaptable to changing requirements. The importance of design in software development cannot be overstated. Software design is complex for a variety of reasons. It is significantly more challenging to teach and learn software design. There have been numerous textbooks created on software design. Most focus on a single program design method, such as object-oriented software development. Few, however, have tackled software design at a higher level of abstraction, such as the methodological level, which is the focus of this subject.

Название: Fundamentals of Programming
Автор: Mir Shehzad Ahmad
Издательство: Toronto Academic Press
Год: 2024
Страниц: 242
Язык: английский
Формат: pdf (true)
Размер: 35.1 MB

This text is a comprehensive guide to computer programming, covering the basic principles, concepts, and techniques of programming. The book provides a detailed overview of programming languages, algorithms, data structures, and software development methodologies. With clear explanations and practical examples, this book is an excellent starting point for anyone interested in learning programming fundamentals. It is an essential resource for students and professionals who want to develop their programming skills and enhance their understanding of Computer Science. Programming refers to the process of creating software or computer programs that can perform specific tasks. It involves using programming languages such as Python, Java, C++, jаvascript, and others to write code that can be executed by a computer. Programming is used in a wide range of applications, including web development, mobile app development, game development, scientific computing, and data analysis. It can involve various programming paradigms, such as procedural, object-oriented, or functional programming. To write effective and efficient code, programmers need to understand programming concepts such as data types, functions, arrays, control structures, algorithms, and data structures. The discussion of the book starts with the fundamentals of programming and software development lifecycle, followed by the evolution and evaluation of different programming languages. Also, the basic concept of algorithms and data structures, along with different data types used in programming, are described in detail in this book.

Название: DataFrame Manipulation: Theory and Applications With Python and Tkinter
Автор: Vivian Siahaan, Rismon Hasiholan Sianipar
Издательство: Balige Publishing
Год: 2024
Страниц: 747
Язык: английский
Формат: epub
Размер: 18.2 MB

A DataFrame is a crucial data structure in Pandas, a versatile Python library for data manipulation and analysis. It is designed to handle two-dimensional, labeled data similar to a spreadsheet or SQL table, facilitating operations such as filtering, sorting, grouping, and aggregating. DataFrames can be created from various data sources, including lists, dictionaries, or NumPy arrays. They offer robust data handling features, including managing missing values and performing input/output operations with diverse file formats. Key capabilities of DataFrames include hierarchical indexing, time series functionality, and integration with libraries like NumPy and Matplotlib, which are essential for efficient data analysis and transforming raw data into actionable insights. Several projects in this book demonstrate practical applications of DataFrames and Tkinter for data analysis. Tkinter-based GUI applications are used in various projects to interact with and visualize data. For instance, one project features a Tkinter GUI that allows users to filter and view sales data interactively, while another enables filtering and viewing of movie data based on release year and rating. Additional projects involve building GUIs to manage and visualize synthetic data for different applications, such as sales, temperature, and medical data. These applications integrate pandas for data manipulation, Tkinter for user interfaces, and Matplotlib for graphical representations, providing comprehensive tools for exploring, analyzing, and visualizing data.

Название: Учебник по функциям Excel и программированию в среде VBA
Автор: С.А. Швыдков
Издательство: МГУ
Год: 2019
Страниц: 105
Язык: русский
Формат: pdf
Размер: 10.1 MB

В книге рассматриваются вопросы применения встроенных функций Excel для решения прикладных задач, а также приводятся начальные сведения языка программирования VBA для Excel. Материал излагается в краткой, доступной форме и иллюстрируется большим количеством наглядных примеров. Учебник предназначен для пользователей, имеющих опыт работы в приложении Excel, но не использующих широких возможностей встроенных функций и программирования в VBA, а также всем интересующимся обработкой информации в Excel. Учебник будет полезен студентам начальных курсов ВУЗов, изучающих информатику. Раздел I данного учебного пособия предназначен для студентов, ознакомленных с возможностями Excel, но не имеющих достаточного опыта в обработке данных с помощью встроенных функций. В этом разделе в краткой форме рассматриваются наиболее востребованные функции из различных категорий (текстовые, логические, статистические...). Применение этих функций наглядно демонстрируется на примерах. Раздел II книги посвящен языку программирования VBA. Предназначен этот раздел для тех, кто имеет некоторый опыт в программировании в других языках, но не решал задач с помощью VBA, а также для тех, кто никогда не программировал, но желает познакомиться с часто встречающейся аббревиатурой VBA.

Название: Нейросети. Обработка аудиоданных
Автор(ы): Картер Д.
Издательство: Литрес/Автор
Год: 2023
Страниц: 123
Формат: pdf, fb2, epub
Размер: 16 Мб
Язык: русский

Эта книга — отличный ресурс для тех, кто желает углубиться в мир аудиоанализа с применением современных методов машинного обучения и нейронных сетей. Подойдет как для начинающих так и для уже опытных пользователей. Вы познакомитесь с распознаванием речи, научитесь создавать акустические модели и оптимизировать их для точного распознавания.

Название: Responsible AI: Implement an Ethical Approach in your Organization
Автор: Olivia Gambelin
Издательство: ‎Kogan Page
Год: 2024
Страниц: 273
Язык: английский
Формат: pdf (true), epub
Размер: 18.9 MB

Responsible AI is a guide to how business leaders can develop and implement a robust and responsible AI strategy for their organizations. Responsible AI has rapidly transitioned to a strategic priority for leaders and organizations worldwide. Responsible AI guides readers step-by-step through the process of establishing robust yet manageable ethical AI initiatives for any size organization, outlining the three core pillars of building a responsible AI strategy: people, process and technology. It provides the insight and guidance needed to help leaders fully understand the technical and commercial potential of ethics in AI while also covering the operations and strategy needed to support implementation. Responsible AI breaks down what it means to use ethics and values as a modern-day decision-making tool in the design and development of AI. It conceptually covers both how ethics can be used to identify risks and establish safeguards in the development of AI and how to use ethics-by-design methods to stimulate AI innovation. It also covers the different considerations for large enterprises and SMEs and discusses the role of the AI ethicist. It is supported by practical case studies from organizations such as IKEA, Nvidia, Rolls-Royce and NatWest Group.

Название: Pandas for Everyone: Python Data Analysis, Second Edition
Автор: Daniel Chen
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2023
Страниц: 512
Язык: английский
Формат: True/Retail (PDF EPUB)
Размер: 64.3 MB

Manage and Automate Data Analysis with Pandas in Python. Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple data sets. Pandas for Everyone, 2nd Edition, brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world data science problems such as using regularization to prevent data overfitting, or when to use unsupervised Machine Learning methods to find the underlying structure in a data set.

Название: Mathematical Models Using Artificial Intelligence for Surveillance Systems
Автор: Padmesh Tripathi, Mritunjay Rai, Nitendra Kumar, Santosh Kumar
Издательство: Wiley-Scrivener
Год: 2024
Страниц: 350
Язык: английский
Формат: pdf (true), epub
Размер: 42.8 MB

This book gives comprehensive insights into the application of Artificial Intelligence (AI), Machine Learning, and Deep Learning in developing efficient and optimal surveillance systems for both indoor and outdoor environments, addressing the evolving security challenges in public and private spaces. Mathematical Models Using Artificial Intelligence for Surveillance Systems aims to collect and publish basic principles, algorithms, protocols, developing trends, and security challenges and their solutions for various indoor and outdoor surveillance applications using Artificial Intelligence (AI). The book addresses how AI technologies such as Machine Learning (ML), Deep Learning (DL), sensors, and other wireless devices could play a vital role in assisting various security agencies. Security and safety are the major concerns for public and private places in every country. Some places need indoor surveillance, some need outdoor surveillance, and, in some places, both are needed. The goal of this book is to provide an efficient and optimal surveillance system using AI, ML, and DL-based image processing. With the emergence of Artificial Intelligence, Machine Learning, and Deep Learning, surveillance systems have reached a standard. It made the surveillance system very powerful and effective in prevention. AI has become increasingly important in surveillance and security applications in recent years. AI is capable of processing and analyzing huge amounts of data in a fast and accurate manner, making it a treasured tool in detection and prevention. One of the most noteworthy benefits of AI-based surveillance systems is their capability to detect and track people and objects accurately. This tool can recognize faces, differentiate between objects and individuals, and identify unusual behavior. AI and ML algorithms can analyze video feeds in real-time, identifying patterns, anomalies, and key details that might go unnoticed by the human eye. They can enable advanced features like facial recognition, license plate recognition, and predictive analytics.

Название: Statistics for Data Science and Analytics
Автор: Peter C. Bruce, Peter Gedeck, Janet Dobbins
Издательство: Wiley
Год: 2025
Страниц: 366
Язык: английский
Формат: pdf (true), epub
Размер: 30.7 MB

Introductory statistics textbook with a focus on Data Science topics such as prediction, correlation, and data exploration. Statistics for Data Science and Analytics is a comprehensive guide to statistical analysis using Python, presenting important topics useful for data science such as prediction, correlation, and data exploration. The authors provide an introduction to statistical science and big data, as well as an overview of Python data structures and operations. A range of statistical techniques are presented with their implementation in Python, including hypothesis testing, probability, exploratory data analysis, categorical variables, surveys and sampling, A/B testing, and correlation. The text introduces binary classification, a foundational element of Machine Learning, validation of statistical models by applying them to holdout data, and probability and inference via the easy-to-understand method of resampling and the bootstrap instead of using a myriad of “kitchen sink” formulas. Regression is taught both as a tool for explanation and for prediction. Python is a general programming language that can be used in many different areas. It is especially popular in the Machine Learning and Data Science communities. A wide range of libraries provide efficient solutions for almost every need, from simple one-off scripts, to web servers, and highly complex scientific applications. As we will see throughout this book, it also has great support for statistics.