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Название: Computational Aspects of Psychometric Methods With R
Автор: Patricia Martinkova, Adela Hladka
Издательство: CRC Press
Год: 2023
Страниц: 348
Язык: английский
Формат: pdf (true)
Размер: 21.8 MB

This book covers the computational aspects of psychometric methods involved in developing measurement instruments and analyzing measurement data in social sciences. It covers the main topics of psychometrics such as validity, reliability, item analysis, item response theory models, and computerized adaptive testing. The computational aspects comprise the statistical theory and models, comparison of estimation methods and algorithms, as well as an implementation with practical data examples in R and also in an interactive ShinyItemAnalysis application. In this book, we use R which is a freely available statistical environment. There are a number of things that make R a great choice for psychometric analysis: Besides being free, it is also open source software, meaning that the code is available for the user, and it is possible to check what a given function does or how the methods are implemented. It offers up-to-date methods as a number of statisticians and researchers from different fields implement the newly published algorithms and methods in R.

Название: Hypergraph Computation
Автор: Qionghai Dai, Yue Gao
Издательство: Springer
Серия: Artificial Intelligence: Foundations, Theory, and Algorithms
Год: 2023
Страниц: 251
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Artificial Intelligence (AI) is now everywhere and fuels both industry and daily life all over the world. We are in the era of “Big Data,” and huge sums of information can be obtained which are too cumbersome for people to process themselves. These Big Data are even with much complex correlations behind them in various areas, such as computer vision and social media. For example, the complex correlations among pixels in an image reveal its semantic information, and different types of correlations among social posts infer the users’ emotions. Therefore, developing effective AI methods to exploit such complex data correlations has become an urgent but challenging task. Graph has been widely used to formulate data correlations. A graph is a non-linear data structure which is composed of groups of vertices and edges, representing the pairwise correlations among vertices. Graph learning and graph neural networks have attracted much attention in both research and industrial fields and become very hot topics in these years. It is noted that the world is far more complex than just pairwise connections, and thus graph-based methods still have limitations on high-order correlation modeling. Hypergraph, as a generation of graph, is able to formulate such high-order correlations among the data and has been investigated in last decades. Recent years have witnessed a great popularity of research on hypergraph-related AI methods, which have been used in computer vision, social media analysis, and etc.

Название: Building Modern Business Applications: Reactive Cloud Architecture for Java, Spring, and PostgreSQL
Автор: Peter Royal
Издательство: Apress
Год: 2023
Страниц: 189
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.2 MB

Discover a new way of thinking about business applications in light of the massive industry shift toward cloud computing and reactive programming technologies. This book synthesizes technologies and techniques such as event sourcing, command query responsibility segregation (CQRS), property-based testing, and GraphQL into a cohesive guide for modern business applications that benefit every developer. The book begins with a look at the fundamentals of modern business applications. These fundamentals include business rules and the managing of data over time. The benefits of reactive techniques are explained, including how they are fundamentally aligned with what application developers strive to achieve in their work. Author Peter Royal equips you with sound guidance to follow as you evolve your existing systems, as well as examples of how to build those systems using modern techniques in Spring, Java, and PostgreSQL.

Название: Data Structures in Java
Автор: Oswald Campesato
Издательство: Mercury Learning and Information
Год: 2023
Страниц: 248
Язык: английский
Формат: pdf (true)
Размер: 10.8 MB

This book is a fast-paced introduction to using data structures with Java. Numerous code samples and listings are included to support myriad topics. The first chapter contains a quick introduction to Java, along with Java code samples to check for leap years, find divisors of a number, and work with arrays of strings. The second chapter introduces recursion and usescode samples to check if a positive number is prime, to find the prime divisors of a positive integer, to calculate the GCD (greatest common divisor) and LCM (lowest common multiple) of a pair of positive integers. The third chapter contains Java code samples involving strings and arrays, such as finding binary substrings of a number, checking if strings contain unique characters, counting bits in a range of numbers, and how to compute XOR without using the XOR function. Chapters 4 through 6 include Java code samples involving search algorithms, concepts in linked lists, and tasks involving linked lists. Finally, Chapter 7 discusses data structures called queues and stacks, along with additional Java code samples.

Название: Edge Intelligence: From Theory to Practice
Автор: Javid Taheri, Schahram Dustdar, Albert Zomaya, Shuiguang Deng
Издательство: Springer
Год: 2023
Страниц: 254
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This graduate-level textbook is ideally suited for lecturing the most relevant topics of Edge Computing and its ties to Artificial Intelligence (AI) and Machine Learning (ML) approaches. The book starts from basics and gradually advances, step-by-step, to ways AI/ML concepts can help or benefit from edge computing platforms. Using practical labs, each topic is brought to earth so that students can practice their learned knowledge with industry-approved software packages. The book is structured into seven chapters; each comes with its own dedicated set of teaching materials (practical skills, demonstration videos, questions, lab assignments, etc.). Chapter 1 opens the book and comprehensively introduces the concept of distributed computing continuum systems that led to the creation of Edge Computing. Chapter 2 motivates the use of container technologies and how they are used to implement programmable edge computing platforms. Chapter 3 introduces ways to employ AI/ML approaches to optimize service lifecycles at the edge. Chapter 4 goes deeper in the use of AI/ML and introduces ways to optimize spreading computational tasks along edge computing platforms.

Название: Создание видеоигр с помощью PyGame - c пошаговыми примерами
Автор: Майк Голд
Издательство: Самиздат
Год: 2023
Страниц: 144
Язык: русский
Формат: pdf +code
Размер: 11,9 MB

Здесь представлен перевод книги Mike Gold - Creating Video Games using PyGame (2023). Добро пожаловать в мир программирования PyGame и Python! Эта книга познакомит вас с библиотекой PyGame и научит вас создавать собственные игры с использованием языка Python. Мы начнем с базового обзора Python и библиотеки PyGame, а затем перейдем к разработке, написанию и отладке нашей собственной игры. От добавления графики и звуков до создания анимации и бонусов — мы расскажем обо всем, что вам нужно знать, чтобы создать собственную насыщенную интерактивную игру. Наконец, мы пройдем процесс отладки и тестирования нашей игры, прежде чем опубликовать ее для всего мира. Итак, давайте начнем и научимся создавать собственные игры с помощью PyGame и Python!

Название: Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi (MEAP v2)
Автор: Marwan Alsabbagh
Издательство: Manning Publications
Год: 2023
Страниц: 147
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Build your first robots with Python and some cheap, basic components. This entertaining book guides you step by step! Build Your Own Robot introduces you to the exciting world of robotics. Your robot isn’t just theory. Beginning in chapter 2 you’ll write code to make your robot move and respond to touch sensors. The book gives accessible advice on available hardware and free open source software that makes creating a robot fun and affordable. Build Your Own Robot is a DIY guide for bringing your first Python-based robots to life. Start with the basics, teaching your new friend how to spin, move around, and find its way. You’ll then quickly progress to controlling your robot remotely using your phone, computer, or joystick. You’ll even set up a camera to broadcast what it sees right to your computer screen. Clever computer vision tricks will get your bot tracking faces, looking for QR codes, and maybe even fetching some snacks. For Python programmers. No previous experience in robotics required.

Название: Bayesian Optimization in Action (MEAP v10)
Автор: Quan Nguyen
Издательство: Manning Publications
Год: 2023
Страниц: 372
Язык: английский
Формат: pdf (true)
Размер: 16.3 MB

Apply advanced techniques for optimizing machine learning processes. Bayesian optimization helps pinpoint the best configuration for your Machine Learning models with speed and accuracy. Bayesian Optimization in Action teaches you how to build Bayesian optimization systems from the ground up. This book transforms state-of-the-art research into usable techniques that you can easily put into practice, all fully illustrated with useful code samples. Hone your understanding of Bayesian optimization through engaging examples—from forecasting the weather, to finding the optimal amount of sugar for coffee, and even deciding if someone is psychic! Along the way, you’ll explore scenarios for when there are multiple objectives, when each decision has its own cost, and when feedback is in the form of pairwise comparisons.

Название: Современный учебник jаvascript в 3 книгах
Автор: Илья Кантор
Издательство: Самиздат
Год: 2 апреля 2023
Страниц: 778+320+474
Язык: русский
Формат: pdf, epub
Размер: 23.3 MB

С помощью этого учебника вы можете изучить jаvascript, начиная с нуля и заканчивая продвинутыми концепциями вроде ООП. Мы будем использовать браузер в качестве окружения, но основное внимание будет уделяться именно самому языку jаvascript. Язык jаvascript изначально был создан для веб-браузеров. Но с тех пор он значительно эволюционировал и превратился в кроссплатформенный язык программирования для решения широкого круга задач. Сегодня jаvascript может использоваться в браузере, на веб-сервере или в какой-то другой среде, даже в кофеварке. Каждая среда предоставляет свою функциональность, которую спецификация jаvascript называет окружением. Окружение предоставляет свои объекты и дополнительные функции, в дополнение базовым языковым. Браузеры, например, дают средства для управления веб-страницами. Node.js делает доступными какие-то серверные возможности и так далее.

Название: Scaling Machine Learning with Spark: Distributed ML with MLlib, TensorFlow, and PyTorch (Final Release)
Автор: Adi Polak
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 294
Язык: английский
Формат: pdf (true), epub (true)
Размер: 14.5 MB

Get up to speed on Apache Spark, the popular engine for large-scale data processing, including Machine Learning and analytics. If you're looking to expand your skill set or advance your career in scalable Machine Learning with MLlib, distributed PyTorch, and distributed TensorFlow, this practical guide is for you. Using Spark as your main data processing platform, you'll discover several open source technologies designed and built for enriching Spark's ML capabilities. This book aims to guide you in your journey as you learn more about Machine Learning (ML) systems. Apache Spark is currently the most popular framework for large-scale data processing. It has numerous APIs implemented in Python, Java, and Scala and is used by many powerhouse companies, including Netflix, Microsoft, and Apple. PyTorch and TensorFlow are among the most popular frameworks for machine learning. Combining these tools, which are already in use in many organizations today, allows you to take full advantage of their strengths. Scaling Machine Learning with Spark examines various technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLFlow, TensorFlow, PyTorch, and Petastorm.