Название: Foundations of Debugging for Golang
Автор: Matt Boyle
Издательство: byteSizeGo
Год: 2024
Страниц: 174
Язык: английский
Формат: pdf, epub
Размер: 34.8 MB

Debugging is the most important skill that most people are never taught. Being able to debug locally and in production is a critical skill for any Go engineer, but it is rarely taught explicitly. It has taken me many years of working with Go in production to get comfortable debugging, and I want to accelerate your learning by teaching you everything I wish I had known when I started out. This book started life as a course and has been written from the ground up, including additional content. When people think of debugging, they often think of the debugger. We will cover how to use the debugger in this book, but it is a small part of our debugging utility belt. Pair Programming is one of the best ways to grow as a Go engineer, especially if you are fortunate enough to pair with someone with more experience than yourself. As the more senior member of a pair, there is still plenty of benefit to you too - we will explore that more below. When I used to work 100% in the office, we used to pair often and I credit it with much of my technical growth. I found moving to remote working has made pairing much harder, but I found a few ways to make it work (although I think the experience is still inferior). If you are a junior or mid-level Go engineer, I think this book will be useful for you.

Название: Ultimate Azure Synapse Analytics: Unlock the Full Potential of Azure Synapse Analytics to Seamlessly Integrate, Analyze, and Optimize Complex Data for Enhanced Business Insights and Decision-Making
Автор: Swapnil Mule
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 847
Язык: английский
Формат: pdf, epub
Размер: 28.5 MB

Empower Your Data Insights with Azure Synapse Analytics. Unlock the full potential of Azure Synapse Analytics with Ultimate Azure Synapse Analytics your definitive roadmap to mastering the art of data analytics in the cloud era. From the foundational concepts to advanced techniques, each chapter offers practical insights and hands-on tutorials to streamline your data workflows and drive actionable insights. Discover how Azure Synapse Analytics revolutionizes data processing and integration, empowering you to harness the vast capabilities of the Azure ecosystem. Seamlessly transition from traditional data warehousing to cutting-edge big data analytics, leveraging serverless and dedicated resources for optimal performance. Dive deep into Synapse SQL, explore advanced data engineering with Apache Spark, and delve into Machine Learning and DevOps practices to stay ahead in today's data-driven landscape. Whether you're seeking to optimize performance, ensure compliance, or facilitate seamless migration, this book provides the expertise needed to excel in your role. Gain valuable insights into industry best practices, enhance your data engineering skills, and drive innovation within your organization. This comprehensive book is crafted for data engineers, analysts, architects, and developers eager to master Azure Synapse Analytics, providing practical insights and advanced techniques. Whether you're a novice or a seasoned professional in the field of data analytics, this book offers invaluable resources to elevate your skills.

Название: 120 практических задач. Создавай нейросети
Автор: Джейд Картер
Издательство: Литрес
Год: 2024
Формат: pdf, epub
Размер: 10 Мб
Качество: Хорошее
Язык: Русский

В книге представлены 120 задач из различных областей, включая анализ данных, прогнозирование, классификацию, распознавание образов и другие. В каждой задаче рассматривается использование глубокого обучения и нейронных сетей для решения, включая выбор архитектуры модели, подготовку данных, обучение и оценку результатов. Примеры кода на Python помогают читателям легко освоить материал и применить его на практике.

Название: Parallel C++: Efficient and Scalable High-Performance Parallel Programming Using HPX
Автор: Patrick Diehl, Steven R. Brandt, Hartmut Kaiser
Издательство: Springer
Год: 2024
Страниц: 233
Язык: английский
Формат: pdf (true), epub
Размер: 26.6 MB

This textbook focuses on practical parallel C++ programming at the graduate student level. In particular, it shows the APIs and related language features in the C++ 17 and C++ 20 standards, covering both single node and distributed systems. It shows that with the parallel features in the C++ 17 and C++ 20 standards, learning meta-languages like OpenMP is no longer necessary. Using the C++ standard library for parallelism and concurrency (HPX), the same language features can be extended to distributed codes, providing a higher-level C++ interface to distributed programming than the Message Passing Interface (MPI). The book starts with the single-threaded implementation of the fractal sets, e.g. Julia set, and Mandelbrot set, using the C++ Standard Library (SL)’s container and algorithms. This code base is used for parallel implementation using low-level threads, asynchronous programming, parallel algorithms, and coroutines. The asynchronous programming examples are then extended to distributed programming using the C++ standard library for parallelism and concurrency (HPX). Octo-Tiger, an astrophysics code for stellar merger, is used as a showcase for a portable, efficient, and scalable high-performance application using HPX. The book’s core audience is advanced undergraduate and graduate students who want to learn the basics of parallel and distributed C++ programming but are not Computer Science majors. Basic C++ knowledge, like functions, classes, loops, and conditional statements, is assumed as a requirement, while C++ advanced topics, like generic programming, lambda functions, smart pointers, and move semantics, are briefly summarized in the appendix.

Название: Advanced Optimization Applications in Engineering
Автор: Afaq Ahmad, Charles V. Camp
Издательство: IGI Global
Год: 2024
Страниц: 308
Язык: английский
Формат: pdf (true), epub
Размер: 45.3 MB

In the ever-evolving landscape of engineering, a pressing challenge looms large—the need to navigate the complexities of modern problems with precision and efficiency. As industries grapple with an array of intricate issues, from sustainable materials to resilient infrastructure, the demand for optimal solutions has never been more pronounced. Traditional approaches are often inadequate, prompting the search for advanced optimization techniques capable of unraveling the intricacies inherent in engineering systems. The problem at hand is clear: how can engineers, researchers, and practitioners harness cutting-edge methodologies to address the multifaceted challenges shaping our technological future? Advanced Optimization Applications in Engineering, is a definitive guide poised to revolutionize problem-solving in civil engineering. This book offers a comprehensive exploration of state-of-the-art optimization algorithms and their transformative applications. By delving into genetic algorithms, particle swarm optimization, neural networks, and other metaheuristic strategies, this collection provides a roadmap for automating design processes, reducing costs, and unlocking innovative solutions. The chapters not only introduce these advanced techniques but also showcase their practical implementation across diverse engineering domains, making this book an indispensable resource for those seeking to stay at the forefront of technological advancements. This book is tailored for a discerning audience comprising engineers, academicians, researchers, practitioners, and students eager to leverage advanced optimization, Artificial Intelligence, and Machine Learning in civil engineering.

Название: Explainable AI Applications for Human Behavior Analysis
Автор: P. Paramasivan, S. Suman Rajest, Karthikeyan Chinnusamy, R. Regin, Ferdin Joe John Joseph
Издательство: IGI Global
Год: 2024
Страниц: 391
Язык: английский
Формат: pdf (true), epub
Размер: 39.4 MB

In the field of Computer Vision research, the study of human behavior is a formidable challenge. The diverse applications of this field, from video surveillance for crowd analysis to healthcare diagnostics, have drawn increasing attention. However, a significant problem persists – the sacrifice of transparency for the sake of predictive accuracy in Artificial Intelligence (AI) solutions. These AI systems often operate as enigmatic black boxes, seemingly conjuring decisions from vast datasets with little to no explanation. The need for clarity and accountability in AI decision-making is paramount as our reliance on these systems continues to grow. Explainable AI Applications for Human Behavior Analysis embarks on a mission to harness AI's innate capability to elucidate upon its own decision-making processes. By focusing on facial expressions, gestures, and body movements, we delve into uncharted territories of research, offering novel methodologies, databases, benchmarks, and algorithms for the analysis of human behavior in natural settings. Geared toward academic scholars, this book compiles the expertise of leading researchers in the field, making it accessible to readers of all educational backgrounds. It bridges the gap between technical depth and ease of comprehension, featuring quick-reference infographics and an array of topics. The aim is not only to inform but also to encourage knowledge sharing among peers. Join us in the exploration of this technology’s transformative potential in decoding human behavior, a journey that promotes clarity, innovation, and accountability for our AI-driven future.

Название: Azure OpenAI Service for Cloud Native Applications: Designing, Planning, and Implementing Generative AI Solutions
Автор: Adrián González Sánchez
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 487
Язык: английский
Формат: epub
Размер: 13.1 MB

Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts.

Название: Internet Modeling with Julia: Models, Algorithms and Programs
Автор: Ulrich Hofmann
Издательство: Springer
Год: 2024
Страниц: 164
Язык: английский
Формат: pdf (true), epub
Размер: 13.1 MB

The book combines internet modeling with the new programming language Julia. It demonstrates Julia's suitability for modeling established internet models and research-oriented topics such as car-to-infrastructure communication and black-box models for load predictions with neural networks. After studying the book and gaining inspiration for further independent analyses, the reader will be able to tackle even more complex modeling tasks in research and development using Julia. In this book, the Julia programming language is used for selected topics of Internet modeling. The “common thread” is the layered architecture of the Internet: from application to technology. For network operators, beyond the technical performance parameters of transmission rate and transmission duration of IP packets, the user satisfaction values Quality of Experience (QoE) with voice, video, haptics transmission are important. With the increase in transmission performance, the old point-to-point lines are also being replaced by packet transmission in the Internet of Things (IoT), and the topic of Quality of Control (QoC) is gaining importance, currently in the area of assisted/autonomous driving. The complex processes on the internet elude exact mathematical White-Box-Model modeling, and approximate learning modeling methods are being intensively researched and integrated into the standards of network architectures. Each chapter begins with a description of the practical background. This is followed by the development of the model and the implementation with Julia, including the a-picture-is-worth-a-thousand-words presentation of results in diagrams. All Julia programs are available for download at GitHub and are labeled with the corresponding figure numbers. The most important pieces of code are explained in the book text.

Название: Machine Learning and Cryptographic Solutions for Data Protection and Network Security
Автор: J. Anitha Ruth, Vijayalakshmi G.V. Mahesh, P. Visalakshi, R. Uma, A. Meenakshi
Издательство: IGI Global
Год: 2024
Страниц: 557
Язык: английский
Формат: pdf (true), epub
Размер: 46.2 MB

In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and Machine Learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage Machine Learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and Machine Learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, Machine Learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. This book is an indispensable guide for scholars navigating the intricate domains of Elliptic Curve Cryptography, Cryptanalysis, Pairing-based Cryptography, Artificial Intelligence, Digital Signature Algorithms, and more. It not only sheds light on current challenges but also provides actionable insights and recommendations, making it an essential resource for those seeking to understand the evolving landscape of data security and actively contribute to its fortification. In a world where the stakes of cybersecurity are higher than ever, this book emerges as a beacon of knowledge, offering a proactive and informed solution to the persistent challenges faced by the research community.

Название: Классические задачи Computer Science на языке Python
Автор: Дэвид Копец
Издательство: Питер
Год: 2021
Cтраниц: 255
Формат: pdf
Размер: 16 мб
Язык: русский

Многие задачи в области Computer Science, которые на первый взгляд кажутся новыми или уникальными, на самом деле уходят корнями в классические алгоритмы, методы кодирования и принципы разработки. И устоявшиеся техники по-прежнему остаются лучшим способом решения таких задач! Научитесь писать оптимальный код для веб-разработки, обработки данных, машинного обучения и других актуальных сфер применения Python.