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Название: Learn C++ by Example: Covers Versions 11 to 23 (Final Release)
Автор: Frances Buontempo
Издательство: Manning Publications
Год: 2024
Страниц: 447
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Learn the latest features of modern C++ by coding eight engaging projects. Don’t let the multitude of C++ updates intimidate you! Learn C++ by Example takes you through the major language changes since C++ 11, with each new feature demonstrated with a fun project or minigame. It’s perfect for beginners who know C++ basics, coders coming back to the language, or current C++ developers missing out on everything the language has to offer. Learn C++ by Example is a fun and practical way to start writing modern C++ code. It guides you through entertaining challenges, emphasizing features and techniques made possible by C++ 17, 20, and 23. You’ll learn about objects and arrays by creating a deck of playing cards, master the C++ random library for a number guess game, use the chrono library to create a countdown timer, and much more. Along the way you’ll also pick up valuable tips for testing, project organization, and other productivity skills.

Название: Effective Software Architecture: Building Better Software Faster (Early Release)
Автор: Oliver Goldman
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2024
Страниц: 223
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB

Effective Software Architecture unites entire software development teams! Effective Software Architecture: Building Better Software Faster is the essential handbook for making software architecture an effective function within organizations and product development processes while putting whole software teams on the same page. Industry elite Oliver Goldman provides a comprehensive perspective on the set of real-world skills and practices this work requires: a predictable, repeatable design process; the ability to make decisions expediently and effectively; a comprehensive and consistent communication strategy; tools that promote efficiency; and a team that is greater than the sum of its parts. This book is for software architects, the managers who lead them, and their counterparts in product management, user experience, program management, and other related disciplines. Building software is a joint space in which all these disciplines cooperate. I hope they will all benefit from these explanations of software architecture as a discipline, its role in software development, and how architects and architecture teams operate.

Название: Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 2
Автор: Atiqur Rahman Ahad, Sozo Inoue, Guillaume Lopez
Издательство: CRC Press
Год: 2024
Страниц: 285
Язык: английский
Формат: pdf (true)
Размер: 18.6 MB

Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects. Activity recognition has been a hot research topic for some years now. One of its main applications is ambient assisted living, so that people in need of assistance might stay in their own environment longer than previously possible. There is a wide range of sensors of different types and applications being tested in this domain, ranging from ambient binary motion sensors and pressure mats to wearable gyroscopes or sensors monitoring body functions. This is also due to the many different levels of surveillance tested by the researchers. The library we selected to use here is Apache Beam and in-memory database Redis. There are two reasons to use Apache Beam: The first is the ease of implementation. Apache Beam can be written in programming languages such as Java or Python, and the process is represented as a pipeline, so it is intuitive and easy to implement. We used Machine Learning methods for classification and extracted statistical features from raw 3-D acceleration and 3-D angular velocity for each axis within the segment. In this work, we compared three types of classifiers, multi-class support vector machine (SVM), Random Forest (RF), and K Nearest Neighbors (KNN) from Scikit-learn, a Machine Learning library for Python. We chose to set all of the parameters of Machine Learning models to default values of Scikit-learn. Before training data with classifiers, we chose RF and KNN classifiers which calculate distances between different points in their algorithm.

Название: Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors: Volume 1
Автор: Atiqur Rahman Ahad, Sozo Inoue, Guillaume Lopez
Издательство: CRC Press
Год: 2024
Страниц: 457
Язык: английский
Формат: pdf (true)
Размер: 21.9 MB

The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. Sensors and cameras are exploited for the analysis and recognition of human activity and behavior. In the book Human Activity and Behavior Analysis: Advances in Computer Vision and Sensors, we have divided across two volumes, 40 wonderful chapters under five parts: Part 1: Healthcare and Emotion (Chapters 1–7), Part 2: Mental Health (Chapters 8–14), Part 3: Nurse Care Records (Chapters 15–26), Part 4: Movement and Sensors (Chapters 27–36), and Part 5: Sports Activity Analysis (Chapters 37–40). In a complex problem such as stress detection, the application of some type of Machine Learning (ML) algorithms makes sense. The vast amount of data in a context where multiple variables, such as HR, HRV, GSR, and ST, might have different outputs based on each other, makes it a prime target for the ML approach. Some of the most common classification algorithms are Support Vector Machines (SVM), K-Nearest Neighbours (K-NN), Random Forests (RF), Decision Trees, and Naive Bayes (NB). The data processing and model development used different Python libraries such as Pandas, Tensorflow, and Keras. To recognize stress from the physiological data, we tested different Machine Learning algorithms. We implemented the approach using Python and the Scikit-learn library.

Название: WOW! Дівчача майстерня
Автор проекта: В.В. Теліцин
Серия: Набір для творчості "Актівіті вирізалочка"
Изд-во: «Апельсин»
Год: 2023
К-во стр.: 32
Формат: pdf
Размер: 40,18 Мб
Язык: українська

Справжня творча майстерня!
Незвичайна і захоплююча книга саморобок – «АКТІВІТІ-ВИРІЗАЛОЧКА». Тут зібрані найцікавіші колекції готових ідей, щоб діти могли власноруч зробити: саморобки, 3D-іграшки, маски, аксесуари, ігри, листівки та інші цікавинки.