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 Название: Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL, 2nd Edition
Автор: James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner
Издательство: Apress
Год: 2023
Страниц: 648
Язык: английский
Формат: pdf (true), epub
Размер: 57.8 MB
Learn how to accelerate C++ programs using data parallelism and SYCL. This book enables C++ programmers to be at the forefront of this exciting and important development that is helping to push computing to new levels. This updated second edition is full of practical advice, detailed explanations, and code examples to illustrate key topics. SYCL enables access to parallel resources in modern accelerated heterogeneous systems. Now, a single C++ application can use any combination of devices–including GPUs, CPUs, FPGAs, and ASICs–that are suitable to the problems at hand. This book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems. The book begins by introducing data parallelism and foundational topics for effective use of SYCL. Later chapters cover advanced topics, including error handling, hardware-specific programming, communication and synchronization, and memory model considerations. If you are new to parallel programming that is okay. If you have never heard of SYCL or the DPC++ compilerthat is also okay. Compared with programming in CUDA, C++ with SYCL offers portability beyond NVIDIA, and portability beyond GPUs, plus a tight alignment to enhance modern C++ as it evolves too. C++ with SYCL offers these advantages without sacrificing performance. C++ with SYCL allows us to accelerate our applications by harnessing the combined capabilities of CPUs, GPUs, FPGAs, and processing devices of the future without being tied to any one vendor. For new data-parallel programming and computer programmers interested in data-parallel programming using C++. | |
Разместил: Ingvar16 3-10-2023, 21:11 | Комментарии: 0 | Подробнее
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 Название: Code to Joy: Why Everyone Should Learn a Little Programming
Автор: Michael L. Littman
Издательство: The MIT Press
Год: 2023
Страниц: 242
Язык: английский
Формат: epub (true), pdf, mobi
Размер: 10.1 MB
How we can get more joy from our machines by telling them what our hearts desire. In this informative, accessible, and very funny book, Michael L. Littman inspires readers to learn how to tell machines what to do for us. Rather than give in to the fear that computers will steal our jobs, spy on us and control what we buy and whom we vote for, we can improve our relationship with them just by learning basic programming skills. Our devices will help us, Littman writes, if we can say what we want in a way they can understand. Each chapter of the book focuses on a particular element of what can be said, providing examples of how we use similar communication in our daily interactions with people. Littman offers ways readers can experiment with these ideas right away, using publicly available systems that might also make us more productive as a welcome side effect. Each chapter also reflects on how the use of these programming components can be expedited by machine learning. With humor and teacherly guidance, Code to Joy brings into view a future where programming is like reading—something everyone can learn. There are some people who believe computer programming is a challenging skill that takes a long time to hone. There are others who are just plain wrong. But advances in Artificial Intelligence and Machine Learning will help the machines meet us partway. These advances will make computer programming more and more like teaching another person. | |
Разместил: Ingvar16 3-10-2023, 17:54 | Комментарии: 0 | Подробнее
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 Название: Knowledge Recommendation Systems with Machine Intelligence Algorithms
Автор: Jaros?aw Protasiewicz
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 139
Язык: английский
Формат: pdf (true), epub
Размер: 13.1 MB
Knowledge recommendation is an urgent and timely topic encountered in research and information services. There is a strongly compelling and urgent need: the modern economy badly requires highly skilled professionals, researchers, and innovators, which enables opportunities to gain competitive advantages and assist in managing financial resources and available goods, as well as carrying out fundamental and applied research more effectively. The design, development, and implementation of the two representative IT systems discussed in the book supplemented with content-based recommendation algorithms illustrate how the paradigm and theory of knowledge recommendation work in practice. This also includes a way of the development and practical application of selected heuristics and Machine Learning/machine intelligence algorithms that aim to create individuals’ expertise profiles and to deliver ways of evaluating enterprise innovation. The book contains an original material and is unique in many ways. The prudent and though-out selection and the exposure of the topics, depth of coverage of the subject matter, and original insights are the focal features of the book. New and promising directions and techniques of Machine Learning applied to knowledge recommendation are original. | |
Разместил: Ingvar16 3-10-2023, 16:56 | Комментарии: 0 | Подробнее
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 Название: Как проектировать программы. Введение в программирование и компьютерные вычисления
Автор: Фелляйзен М., Финдлер Р. Б., Флэтт М., Кришнаму Ш.
Издательство: ДМК Пресс
Год: 2022
Cтраниц: 724
Формат: pdf
Размер: 21 мб
Язык: русский
Эта книга повествует о методах «хорошего программирования» – то есть о таком подходе к созданию программного обеспечения, который опирается на системное мышление, планирование и понимание задач разработчика на каждом этапе. В числе рассматриваемых тем – фундаментальные понятия систематического проектирования, типы данных, способы записи объемных данных, создание и использование абстракций, тестирование программ и функций и др. Издание адресовано профессионалам и энтузиастам программирования, не имеющим прежнего опыта систематического проектирования программ, а также преподавателям технических вузов, которые могут использовать представленный материал в рамках учебного курса. | |
Разместил: rivasss 3-10-2023, 11:58 | Комментарии: 0 | Подробнее
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 Название: Advanced Guide to Python 3 Programming, 2nd Edition
Автор: John Hunt
Издательство: Springer
Год: 2023
Страниц: 638
Язык: английский
Формат: pdf (true), epub
Размер: 46.0 MB
Advanced Guide to Python 3 Programming 2nd Edition delves deeply into a host of subjects that you need to understand if you are to develop sophisticated real-world programs. Each topic is preceded by an introduction followed by more advanced topics, along with numerous examples, that take you to an advanced level. This second edition represents a significant expansion of the material in the first edition, as well as an update of that book from Python 3.7 to 3.12. This book includes whole new sections on advanced language features, Reactive Programming in Python and data analysts. New chapters on working with Tkinter, on event handling with Tkinter and a simple drawing application using Tkinter have been added. A new chapter on performance monitoring and profiling has also been added. A chapter on pip and conda is included at the end of the book. In all there are 18 completely new chapters that take you far further on your Python journey. I have heard many people over the years say that Python is an easy language to learn and that Python is also a simple language. To some extent both of these statements are true; but only to some extent. While the core of the Python language is easy to lean and relatively simple (in part thanks to its consistency), the sheer richness of the language constructs and flexibility available can be overwhelming. | |
Разместил: Ingvar16 3-10-2023, 08:34 | Комментарии: 0 | Подробнее
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 Название: The Python Interview Handbook 2023 : Your Ultimate Guide to Crack Any Python Interview with 500 Q & A
Автор: Nezir Zahirovic
Издательство: Leanpub
Год: 2023-06-09
Страниц: 250
Язык: английский
Формат: pdf
Размер: 25.1 MB
If you're looking for a comprehensive guide to prepare for Python interviews, The Python Interview Handbook 2023 is the perfect resource for you. This book is a must-read for anyone who wants to excel in Python interviews, and it covers more than 500 interview questions and answers about Python. Python has been one of the most popular programming languages in recent years, and it has become an essential skill for software developers, data scientists, and machine learning engineers. However, getting a job in these fields requires more than just knowing the basics of Python. You need to demonstrate your knowledge, skills, and expertise in Python during the interview process. If you're looking for a comprehensive guide to prepare for Python interviews, The Python Interview Handbook 2023 is the perfect resource for you. This book is a must-read for anyone who wants to excel in Python interviews, and it covers more than 500 interview questions and answers about Python, testing, deployment, machine learning, microservices, code samples, architecture, databases, algorithms, and more. | |
Разместил: Ingvar16 3-10-2023, 07:58 | Комментарии: 0 | Подробнее
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 Название: Machine Learning in Python for Dynamic Process Systems: A practitioner’s guide for building process modeling, predictive, and monitoring solutions using dynamic data
Автор: Ankur Kumar, Jesus Flores-Cerrillo
Издательство: Leanpub
Год: June 2023
Страниц: 208
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
This book provides a comprehensive coverage of Machine Learning (ML) methods that have proven useful in process industry for dynamic process modeling. Step-by-step instructions, supported with industry-relevant case studies, show (using Python) how to develop solutions for process modeling, process monitoring, etc., using classical and modern methods. This book is designed to help readers gain a working-level knowledge of machine learning-based dynamic process modeling techniques that have proven useful in process industry. Readers can leverage the concepts learned to build advanced solutions for process monitoring, soft sensing, inferential modeling, predictive maintenance, and process control for dynamic systems. The application-focused approach of the book is reader friendly and easily digestible to the practicing and aspiring process engineers, and data scientists. No prior experience with Machine Learning or Python is needed. Undergraduate-level knowledge of basic linear algebra and calculus is assumed. | |
Разместил: Ingvar16 3-10-2023, 07:40 | Комментарии: 0 | Подробнее
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 Название: Attention Augmented Learning Machines: Theory and Applications
Автор: Guoqiang Zhong, Jinxuan Sun
Издательство: Nova Science Publishers, Inc.
Год: 2023
Страниц: 140
Язык: английский
Формат: pdf (true)
Размер: 35.6 MB
Deep Learning has developed for more than 10 years. Many novel models are proposed. Among others, the attention models have greatly impacted the Deep Learning area. Similar to the attention mechanism of human beings, the attention mechanism improves the performance of many Deep Learning models based on its discovery of important information hidden in data and motivates the emergence of many new Deep Learning models, like Transformer and its variants. This book includes eight chapters and aims to introduce some interesting works on the attention mechanism. Chapter 1 is a review of the attention mechanism used in the Deep Learning area, while Chapters 2 and 3 present two models that integrate the attention mechanism into gated recurrent units (GRUs) and long short-term memory (LSTM), respectively, making them pay attention to important information in the sequences. This book can be used by college students (undergraduate or graduate) chosen to major in Computer Science, Artificial Intelligence, electrical engineering, and mathematics, or others who study or have the potential to use Deep Learning algorithms. It could be of special interest to professors who research pattern recognition, Machine Learning, computer vision, neural language processing (NLP), and related fields, or engineers who apply Deep Learning models to their products. On the other hand, the reader is assumed to be already familiar with basic computer programming, Machine Learning, pattern recognition, and computer vision. | |
Разместил: Ingvar16 3-10-2023, 07:14 | Комментарии: 0 | Подробнее
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 Название: x64 Assembly Language Step-by-Step: Programming with Linux (Tech Today), 4th Edition
Автор: Jeff Duntemann
Издательство: Wiley
Год: 2024
Страниц: 636
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.5 MB, 13.0 MB
The long-awaited x64 edition of the bestselling introduction to Intel assembly language. In the newly revised fourth edition of x64 Assembly Language Step-by-Step: Programming with Linux, author Jeff Duntemann delivers an extensively rewritten introduction to assembly language with a strong focus on 64-bit long-mode Linux assembler. The book offers a lighthearted, robust, and accessible approach to a challenging technical discipline, giving you a step-by-step path to learning assembly code that's engaging and easy to read. x64 Assembly Language Step-by-Step makes quick work of programmable computing basics, the concepts of binary and hexadecimal number systems, the Intel x86/x64 computer architecture, and the process of Linux software development to dive deep into the x64 instruction set, memory addressing, procedures, macros, and interface to the C-language code libraries on which Linux is built. A one-stop resource for aspiring and practicing Intel assembly programmers, the latest edition of this celebrated text provides readers with an authoritative tutorial approach to x64 technology that's ideal for self-paced instruction. | |
Разместил: Ingvar16 2-10-2023, 15:05 | Комментарии: 1 | Подробнее
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 Название: Gradient Expectations: Structure, Origins, and Synthesis of Predictive Neural Networks
Автор: Keith L. Downing
Издательство: The MIT Press
Год: 2023
Страниц: 224
Язык: английский
Формат: epub (true)
Размер: 15.4 MB
An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI. Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems. Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today’s Deep Learning. | |
Разместил: Ingvar16 2-10-2023, 04:31 | Комментарии: 0 | Подробнее
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