Название: Generalized Kernel Equating with Applications in R
Автор: Marie Wiberg, Jorge González, Alina A. von Davier
Издательство: CRC Press
Год: 2025
Страниц: 267
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Generalized Kernel Equating is a comprehensive guide for statisticians, psychometricians, and educational researchers aiming to master test score equating. This book introduces the Generalized Kernel Equating (GKE) framework, providing the necessary tools and methodologies for accurate and fair score comparisons. The book presents test score equating as a statistical problem and covers all commonly used data collection designs. It details the five steps of the GKE framework: presmoothing, estimating score probabilities, continuization, equating transformation, and evaluating the equating transformation. Various presmoothing strategies are explored, including log-linear models, item response theory models, beta4 models, and discrete kernel estimators. The estimation of score probabilities when using IRT models is described and Gaussian kernel continuization is extended to other kernels such as uniform, logistic, epanechnikov and adaptive kernels. Several bandwidth selection methods are described. The kernel equating transformation and variants of it are defined, and both equating-specific and statistical measures for evaluating equating transformations are included. Real data examples, guiding readers through the GKE steps with detailed R code and explanations are provided. Readers are equipped with an advanced knowledge and practical skills for implementing test score equating methods.

Название: Конструкторская разработка изобретения
Автор: Гущин В.Ф.
Издательство: Лениздат
Год издания: 1967
Количество страниц: 126
Язык: русский
Формат: DJVU, PDF
Размер: 10,13 Мб

В брошюре рассматриваются вопросы, с которыми приходится сталкиваться рабочему - изобретателю и рационализатору при конструктивном оформлении своих технических идей. В ней приводятся рекомендации по выбору рациональной последовательности конструкторской разработки изобретения, освещаются вопросы методики конструирования, обеспечения технологичности разрабатываемой конструкции, ее надежности, долговечности и взаимозаменяемости. Ознакомление с этой брошюрой должно подготовить читателя к работе над остальными брошюрами Библиотечки, в которых освещаются вопросы расчетного обоснования конструкций.
Брошюра рассчитана па читателя, имеющего образование в объеме 8 классов средней школы, и может быть также полезна конструкторам машино- и приборостроения.

Название: Основы научно-технического творчества, изобретательской и рационализаторской работы
Автор: А.И. Фурсенко, С.В. Романовский, Д.М. Беренштейн
Издательство: Высшая школа
Год издания: 1987
Количество страниц: 194
Язык: русский
Формат: DjVu
Размер: 10,14 Мб

В книге рассмотрены отдельные вопросы теории и методики изобретательства, а также организации научно-технического творчества, экспериментально-конструкторской работы в средних специальных учебных заведениях, изложены основные методы оптимального решения научно-технических задач, даны рекомендации по активизации творческого процесса.

Название: Трактор, комбайн, автомобиль - в умелые руки
Автор: Трушкин В.П.
Издательство: Московский рабочий
Год издания: 1985
Количество страниц: 194
Язык: русский
Формат: DjVu
Размер: 10,12 Мб

Настоящая книга, получившая многочисленные положительные отклики читателей, выпускается уже третьим дополненным изданием. В ней содержится много необходимых полезных сведений о конструктивных особенностях тракторов, комбайнов, автомобилей, советов по их регулировке и эффективной эксплуатации.
Рассчитана на широкий круг механизаторов совхозов и колхозов.

Название: Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pipelines and Cloud Platforms
Автор: Pavan Kumar Narayanan
Издательство: Apress
Год: 2024
Страниц: 631
Язык: английский
Формат: pdf
Размер: 33.0 MB

This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code. The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask's capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows. What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. For data analysts, data engineers, data scientists, Machine Learning engineers, and MLOps specialists.

Название: Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib, 3rd Edition
Автор: Robert Johansson
Издательство: Apress
Год: 2024
Страниц: 485
Язык: английский
Формат: pdf
Размер: 24.5 MB

Learn how to leverage the scientific computing and data analysis capabilities of Python, its standard library, and popular open-source numerical Python packages like NumPy, SymPy, SciPy, Matplotlib, and more. This book demonstrates how to work with mathematical modeling and solve problems with numerical, symbolic, and visualization techniques. It explores applications in science, engineering, data analytics, and more. Numerical Python, Third Edition, presents many case study examples of applications in fundamental scientific computing disciplines, as well as in Data Science and statistics. This fully revised edition, updated for each library's latest version, demonstrates Python's power for rapid development and exploratory computing due to its simple and high-level syntax and many powerful libraries and tools for computation and data analysis. After reading this book, readers will be familiar with many computing techniques, including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling, and Machine Learning. For developers who want to understand how to use Python and its ecosystem of libraries for scientific computing and data analysis.

Название: Open-Source Security Operations Center (SOC): A Complete Guide to Establishing, Managing, and Maintaining a Modern SOC
Автор: Alfred Basta, Nadine Basta, Waqar Anwar, Mohammad Ilyas Essar
Издательство: Wiley
Год: 2025
Страниц: 480
Язык: английский
Формат: pdf, azw3, epub (true), mobi
Размер: 10.1 MB

A comprehensive and up-to-date exploration of implementing and managing a security operations center in an open-source environment. In Open-Source Security Operations Center (SOC): A Complete Guide to Establishing, Managing, and Maintaining a Modern SOC, a team of veteran cybersecurity practitioners delivers a practical and hands-on discussion of how to set up and operate a security operations center (SOC) in a way that integrates and optimizes existing security procedures. You'll explore how to implement and manage every relevant aspect of cybersecurity, from foundational infrastructure to consumer access points. In the book, the authors explain why industry standards have become necessary and how they have evolved – and will evolve – to support the growing cybersecurity demands in this space. SOCs use a variety of tools and technologies, including security information and event management (SIEM) systems, intrusion detection and prevention systems (IDPSs), threat intelligence platforms, and endpoint detection and response (EDR) solutions, to accomplish the objectives they want to achieve. SOC team members utilize these technologies to detect, investigate, and respond to security incidents. Perfect for cybersecurity practitioners and software engineers working in the industry, Open-Source Security Operations Center (SOC) will also prove invaluable to managers, executives, and directors who seek a better technical understanding of how to secure their networks and products.

Название: Human-Robot Interaction: An Introduction, 2nd Edition
Автор: Christoph Bartneck, Tony Belpaeme, Friederike Eyssel, Takayuki Kanda
Издательство: Cambridge University Press
Год: 2024
Страниц: 323
Язык: английский
Формат: pdf (true)
Размер: 24.0 MB

The role of robots in society keeps expanding and diversifying, bringing with it a host of issues surrounding the relationship between robots and humans. This introduction to human–robot interaction (HRI) by leading researchers in this developing field is the first to provide a broad overview of the multidisciplinary topics central to modern HRI research. Written for students and researchers from robotics, Artificial Intelligence (AI), psychology, sociology, and design, it presents the basics of how robots work, how to design them, and how to evaluate their performance. Self-contained chapters discuss a wide range of topics, including speech and language, nonverbal communication, and processing emotions, plus an array of applications and the ethical issues surrounding them. This revised and expanded second edition includes a new chapter on how people perceive robots, coverage of recent developments in robotic hardware, software, and Artificial Intelligence, and exercises for readers to test their knowledge. Middleware is software that sits among software components, such as commonly available library modules and the application modules that the developers created for a specific purpose, as well as the operating system of the robot’s computer. It is often considered as the “software glue” because its function is to ease the connection of those software components. The Robot Operating System (ROS) is a middleware platform commonly used in the robotics and HRI community. Computer Vision is an important area for HRI. Another computer-vision technique relevant to HRI is the processing of faces. The ability to detect faces in an image has advanced and can be used, for example, to let the robot look people in the eye. Face recognition is still a challenge, however. Impressive progress has been made in the last decade, mainly fueled by the evolution of Deep Learning, and it is now possible to reliably recognize and distinguish between hundreds of people when they are facing the camera.

Название: Business Intelligence, Analytics, Data Science, and AI: A Managerial Perspective, 5th Edition
Автор: Ramesh Sharda, Dursun Delen, Efraim Turban
Издательство: Pearson Education, Inc.
Год: 2024
Страниц: 727
Язык: английский
Формат: pdf (true)
Размер: 39.2 MB

Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of Artificial Intelligence (AI), Data Science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager. The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and “data for good.” Hadoop is an open-source framework for processing, storing, and analyzing massive amounts of distributed, unstructured data. A related new style of database called NoSQL (Not Only SQL) has emerged to, like Hadoop, process large volumes of multistructured data. Evolving out of the traditional artificial neural networks (ANN), Deep Learning is changing the very foundation of how Machine Learning works. Thanks to large collections of data and improved computational resources, Deep Learning is making a profound impact on how computers can discover complex patterns using the self-extracted features from the data (as opposed to a data scientist providing the feature vector to the learning algorithm).

Название: Deep Learning for 3D Vision: Algorithms and Applications
Автор: Xiaoli Li, Xulei Yang, Hao Su
Издательство: World Scientific Publishing
Год: 2024
Страниц: 493
Язык: английский
Формат: pdf (true)
Размер: 20.9 MB

3D Deep Learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D Deep Learning, covering a wide range of research topics and applications. It collates the most recent research advances in 3D Deep Learning, including algorithms and applications, with a focus on efficient methods to tackle the key technical challenges in current 3D Deep Learning research and adoption, therefore making 3D Deep Learning more practical and feasible for real-world applications. For any AI-enabled agent to accomplish its task, visual understanding or perception is the first step towards interacting with the three-dimensional (3D) world. Due to its inherent limitations, visual understanding techniques based solely on two-dimensional (2D) images may be inadequate for real-world applications. This calls for 3D Deep Learning techniques that operate on 3D data, which enables a direct visual understanding of the 3D world. In recent years, 3D Deep Learning has been attracting increasing attention. As we live in a 3D world, 3D Deep Learning is a natural way to perceive and understand our environment, enabling emerging and new industrial applications, such as autonomous driving, robot perception, medical imaging, and scientific simulations, and many more. In the context of 3D Deep Learning, deep neural networks have been adapted and extended to work with 3D data, including point clouds, meshes, and volumetric data. This has led to significant progress in tasks, such as 3D object detection and segmentation, point cloud classification, and 3D reconstruction.