Название: Quick Start Kubernetes (2023 Edition)
Автор: Nigel Poulton
Издательство: Leanpub
Год: 2023-01-18
Страниц: 164
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB

Do you need to figure out what Kubernetes is all about? Do you like learning through hands-on? If yes, this is the book for you... Quick Start Kubernetes, brought to you by best-selling author Nigel Poulton, assumes zero prior experience and gets you to the point you can hold your own in a conversation with an expert, and deploy simple applications. You’ll learn why we have Kubernetes, what it is, and where it’s going. On the theory front, you’ll learn about microservices, orchestration, why Kubernetes is the OS of the cloud, and the architecture of a Kubernetes cluster. On the hands-on front, you’ll have the opportunity to build a cluster, containerize an app, deploy it, break it, see Kubernetes fix it, scale it, and perform an application update. And as this is a quick start guide, you’ll be up-to-speed in no time at all.

Название: С++ 20 в деталях
Автор: Райнер Гримм
Издательство: ДМК Пресс
Год: 2023
Страниц: 519
Язык: русский
Формат: pdf
Размер: 33.3 MB

В этой книге подробно рассказывается о новом стандарте С++20. Для тех, кто не знаком с С++20, приводится краткий обзор, далее рассматриваются ключевые возможности языка. Вы получите представление о ключевых изменениях в ядре языка (концепты и модули), новой библиотеке диапазонов, корутинах, а затем сможете применить теорию на практике, изучив ряд примеров. Книгу можно использовать как справочное руководство и изучать главы в удобном для вас порядке. Издание будет полезно разработчикам, желающим освоить последнюю версию С++, изучить передовые возможности и добавления в язык, а также заглянуть за кулисы разработки новых стандартов языка и узнать, как предлагаются, обсуждаются и утверждаются новые изменения в стандарт С++ и чем вызваны эти изменения.

Название: Convex Optimization for Machine Learning
Автор: Changho Suh
Издательство: Now Publishers Inc
Год: 2022
Страниц: 379
Язык: английский
Формат: pdf (true)
Размер: 11.2 MB

This book covers an introduction to convex optimization, one of the powerful and tractable optimization problems that can be efficiently solved on a computer. The goal of the book is to help develop a sense of what convex optimization is, and how it can be used in a widening array of practical contexts with a particular emphasis on Machine Learning. The first part of the book covers core concepts of convex sets, convex functions, and related basic definitions that serve understanding convex optimization and its corresponding models. The second part deals with one very useful theory, called duality, which enables us to: (1) gain algorithmic insights; and (2) obtain an approximate solution to non-convex optimization problems which are often difficult to solve. The last part focuses on modern applications in Machine Learning and Deep Learning. We employ Python as a major programming platform. To solve traditional convex optimization problems such as linear program, least squares, and semi-definite program, we utilize an easy-to-use and high-level language, CVXPY, running in Python. To implement Machine Learning and Deep Learning algorithms, we employ TensorFlow, one of the most popular Deep Learning frameworks.

Название: Numerical Methods in Chemical Engineering Using Python and Simulink
Автор: Nayef Ghasem
Издательство: CRC Press
Год: 2024
Страниц: 371
Язык: английский
Формат: pdf (true)
Размер: 38.6 MB

Numerical methods are vital to the practice of chemical engineering, allowing for the solution of real-world problems. Written in a concise and practical format, this textbook introduces readers to the numerical methods required in the discipline of chemical engineering and enables them to validate their solutions using both Python and Simulink. Numerical analysts and mathematicians use a variety of tools to develop numerical methods for solving mathematical problems. The most crucial idea mentioned earlier, which includes all mathematical problems, is to change a particular problem into one that can be easily solved. Other ideas vary about the type of mathematical problem that was solved.

Название: Foundations of Probabilistic Logic Programming: Languages, Semantics, Inference and Learning, 2nd Edition
Автор: Fabrizio Riguzzi
Издательство: River Publishers
Серия: River Publishers Series in Software Engineering
Год: 2023
Страниц: 548
Язык: английский
Формат: pdf (true)
Размер: 34.7 MB

The computational foundations of Artificial Intelligence (AI) are supported by two comer stones: logics and Machine Leaming. Computationallogic has found its realization in a number of frameworks for logic-based approaches to knowledge representation and automated reasoning, such as Logic Program­ ming, Answer Set Programming, Constraint Logic Programming, Descrip­tion Logics, and Temporal Logics. Machine Leaming, and its recent evolution to Deep Leaming, has a huge number of applications in video surveillance, social media services, Big Data analysis, weather predictions, spam filtering, online customer support, etc. Since its birth, the field of Probabilistic Logic Programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. The intended audience of the book are researchers in Computer Science and AI that want to getan overview of PLP. However, it can also be used by students, especially graduate, to get acquainted with the topic, and by practitioners that would like to get more details on the inner workings of methods.

Название: The fundamentals of algorithmic processes
Автор: Sourabh Pal
Издательство: Arcler Press
Год: 2023
Страниц: 271
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book focuses on the creative elements of algorithmic design by delving into the phases involved in algorithm creation. The conceptual underpinnings of this creative process are analogous to the invention and development of mathematical theorems that result in the induction of combinatorial algorithms. Numerous issue examples are included in the book. It is intended to enhance readers' problem-solving abilities by imparting a grasp of the fundamental ideas behind algorithmic design. This book summarizes the most widely used computer algorithms and provides a comprehensive overview of algorithms and data structures for searching, sorting, and graph processing. The algorithms presented in this book represent a body of knowledge that has developed over the previous five decades and has become critical not just for professional programmers and computer scientists, but also for all students interested in mathematics, data science, and engineering. The reader of this book is meant to get knowledge about known ways for successfully resolving difficulties. They will become acquainted with various cutting-edge data structures and novel methods for utilizing data structures to improve the efficacy of algorithms. Because the book is virtually self-contained, it may be used as a course book, reference book, or self-study resource. This book provides a comprehensive summary of contemporary research on computer algorithms. The book contains a detailed discussion of several sorts of computer algorithms. The information on algorithm creation and analysis is meant for a broad audience. A fundamental understanding of programming languages and mathematics are required to conduct algorithmic analysis.

Название: Concurrent, parallel and distributed computing
Автор: Adele Kuzmiakova
Издательство: Arcler Press
Год: 2023
Страниц: 260
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The book "Concurrent, Parallel, and Distributed Computing" offers an excellent overview of the various areas of the computing field. There is a lot of overlap between the words "concurrent computing," "parallel computing," and "distributed computing," and there is no obvious differentiation between them. The same system can be described as "parallel" and "distributed"; in a typical distributed system, the processors run concurrently in parallel.The content in the book is presented in such a way that even a reader with no prior knowledge of computers may understand it and become acquainted with the fundamental concepts of computing. It offers numerous small examples, demonstration materials, and sample exercises that teachers can use to teach parallel programming principles to students who have just recently been introduced to basic programming concepts. It focuses on Python multiprocessing features like fork/join threading, message passing, sharing resources between threads, and using locks. Parallelism's utility can be seen in applications like searching, sorting, and simulations. Students and researchers can get an accessible and comprehensive explanation of the concepts, guidelines, and, in particular, the complex instrumentation techniques used in computing.

Название: Data Structure and Algorithm
Автор: Nikhat Raza Khan, Manmohan Singh, Piyush Kumar
Издательство: Arcler Press
Год: 2023
Страниц: 342
Язык: английский
Формат: pdf (true)
Размер: 19.4 MB

Data structure and algorithms are two of the most important aspects of Computer science. Data structure and algorithms help in understanding the nature of the problem at a deeper level and thereby a better understanding of the world. Learning data structure and algorithms will help you become a better programmer. This book provides a comprehensive introduction to the modern study of computer algorithms. It presents many algorithms and covers them in considerable depth, which makes their design and analysis accessible to all levels of readers. This book provides with an enjoyable introduction to the field of algorithms. This book provides a comprehensive introduction to the modern study of computer algorithms. It presents many algorithms and covers them in considerable depth, which makes their design and analysis accessible to all levels of readers. We have tried to keep explanations elementary without sacrificing depth of coverage or accuracy. Each chapter presents an algorithm, a design technique, an application area, or a related topic. Algorithms are described in English and in a “pseudocode” designed to be readable by anyone who has done a little programming. The book contains over 300 pages with facts and figures illustrating how the algorithms work. Since we emphasize efficiency as a design criterion, we include careful analyzes of the running times of all our algorithms. Since we emphasize efficiency as a design criterion, we include careful analyzes of the running times of all our algorithms.

Название: Rise of Generative AI and ChatGPT: Understand how Generative AI and ChatGPT are transforming and reshaping the business world
Автор: Utpal Chakraborty, Soumyadeep Roy, Sumit Kumar
Издательство: BPB Publications
Год: 2023
Страниц: 290
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

Generative AI and ChatGPT have the potential to transform industries and society by improving efficiency, enhancing creativity, and enabling more personalized experiences. If you are someone who is looking to stay ahead of the curve in this rapidly evolving digital age and utilize its potential, this book is for you. This book gives a comprehensive overview of Generative AI and ChatGPT, the cutting-edge technologies that have gained significant attention in recent times. The book aims to provide a thorough understanding of these technologies, architectures, and training methods, including their background, development process, and current state. The book helps discover innovative ways in which these technologies have been implemented to achieve measurable benefits, including improved efficiency, customer satisfaction, security, and revenue growth and its potential application across different industries and use cases.

Название: Optimization for Learning and Control
Автор: Martin Andersen, Anders Hansson
Издательство: Wiley
Год: 2023
Страниц: 435
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Optimization for Learning and Control Comprehensive resource providing a masters’ level introduction to optimization theory and algorithms for learning and control. Optimization for Learning and Control describes how optimization is used in these domains, giving a thorough introduction to both Unsupervised Learning, Supervised Learning, and Reinforcement Learning, with an emphasis on optimization methods for large-scale learning and control problems. Several applications areas are also discussed, including signal processing, system identification, optimal control, and Machine Learning. Today, most of the material on the optimization aspects of Deep Learning that is accessible for students at a Masters’ level is focused on surface-level computer programming; deeper knowledge about the optimization methods and the trade-offs that are behind these methods is not provided. The objective of this book is to make this scattered knowledge, currently mainly available in publications in academic journals, accessible for Masters’ students in a coherent way. The focus is on basic algorithmic principles and trade-offs.