Название: Linux Kernel Programming: Developing kernel architecture and device drivers for character, block, USB, and network interfaces
Автор: Thierry Gayet
Издательство: BPB Publications
Год: 2025
Страниц: 558
Язык: английский
Формат: epub (true)
Размер: 13.8 MB

Linus Torvald released the first version of a kernel in 1991, inspired at the time by both proprietary Unix and the Minix system. Thirty-four years later, this system has evolved with stability and robustness, making it almost indispensable for the DevSecOps community. The Linux kernel forms the robust core of countless systems, from embedded devices to vast data centers, driving unparalleled power and flexibility. This book is your essential guide to deeply understanding this fundamental component and mastering the art of developing high-performance kernel-level code. This book meticulously details the kernel's history, architectural evolution, and custom build processes. You will master device driver fundamentals, distinguishing user from kernel space, and understanding the Linux Device Model (LDM). The guide concludes with task/process management, real-time concepts, and essential kernel debugging and profiling. By the end of this book, you will be well-equipped to confidently develop, optimize, and debug kernel-level code. This book is for software engineers looking to understand the Linux kernel's architecture, modify it, and develop custom modules.

Название: The AI Pocket Book
Автор: Emmanuel Maggiori
Издательство: Manning Publications
Год: 2025
Страниц: 200
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

If you’re worried about your tech career going obsolete in a world of super-powered AI, never fear. The AI Pocket Book crams everything engineers need to know about AI into one short volume you can fit into your pocket. You’ll build a better understanding of AI (and its limitations), learn how to use it more effectively, and future-proof your job against its advancement. The AI Pocket Book takes a peek inside the AI black box and gives you just enough on key topics like transformers, hallucinations, and the modern ecosystem of AI models and tools. You’ll get handy techniques to select AI tools, learn when putting AI first is the smart move, and pick up some excellent tips for managing the inevitable, potentially expensive, screw ups. The first part of this chapter is a high-level explanation of how large language models (LLMs) such as ChatGPT work. Two main groups of people should read this book. The first one is software engineers—aspiring, novice, and seasoned ones—who want to understand the effects of AI on their careers and prepare for it. The second group includes people related to or interested in the software industry, even if they’re not engineers themselves.

Название: Software Performance Engineering: A comprehensive guide for high-performance development
Автор: Alon Rotem
Издательство: BPB Publications
Год: 2025
Страниц: 521
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

This book introduces the concept of Software Performance Engineering throughout the development process. Software performance yields from a wide range of factors: from hardware through coding standards, runtime frameworks, design patterns, quality assurance and testing, and system architectural patterns, to name a few. This book takes a holistic view of the entire software development lifecycle, learning each of its phases, to understand the technologies, techniques, and tools available, and how we can use them to improve the behavior and performance of our system. Technical hands-on chapters introduce tools and libraries, showing practical examples of how to set them up and use them with ease, while theoretical chapters include comprehensive information and deep explanations of a broad selection of concepts, all accompanied by relevant charts, screenshots, and code samples. Code snippets are mainly written in Python, as the book focuses on current technologies, delving into concepts of cloud computing, design patterns, and best practices, in order to learn how to optimize the entire software delivery process, end-to-end.

Название: Applied TinyML: End-to-end machine learning for microcontrollers with examples
Автор: Ricardo Cid
Издательство: BPB Publications
Год: 2025
Страниц: 371
Язык: английский
Формат: epub (true)
Размер: 16.8 MB

AI is useful when it runs in large machines in data centers, but only when it makes it down to stand-alone edge devices will it unlock countless new use cases and applications. TinyML is transforming AI by bringing ML capabilities to small, low-power devices at the very edge of the network. This book will guide you through building these smart devices. It establishes TinyML's core foundations and a methodology for application development, from problem definition to power management and cost analysis. You will explore practical skills applications, learning sound, movement, and image classification, followed by advanced techniques like object tracking and sensor fusion, using methods such as Kalman filters. You will explore deep learning regression for predictive tasks and essential anomaly detection for identifying unusual patterns, all demonstrated through real-world use cases. This book is for engineers, developers, and AI enthusiasts eager to build intelligent edge devices. No prior deep expertise in AI or electronics is required; it is perfect for anyone starting their journey in creating smart widgets with TinyML.

Название: Deep Learning in Modern C++: End-to-end development and implementation of deep learning algorithms
Автор: Luiz Carlos d'Oleron
Издательство: BPB Publications
Год: 2025
Страниц: 525
Язык: английский
Формат: epub (true)
Размер: 36.0 MB

Deep learning is revolutionizing how we approach complex problems, and harnessing its power directly within C++ provides unparalleled control and efficiency. This book bridges the gap between cutting-edge Deep Learning techniques and the robust, high-performance capabilities of modern C++, empowering developers to build sophisticated AI applications from the ground up. This book guides you through the entire development lifecycle, starting with a solid foundation in the modern features and essential libraries, like Eigen, for C++. You will master core Deep Learning concepts by implementing convolutions, fully connected layers, and activation functions, while learning to optimize models using gradient descent, backpropagation, and advanced optimizers like SGD, Momentum, RMSProp, and Adam. Crucial topics like cross-validation, regularization, and performance evaluation are covered, ensuring robust and reliable applications. This book is tailored for C++ developers, data scientists, and Machine Learning engineers seeking to implement Deep Learning models using modern C++. A foundational understanding of C++ programming and basic linear algebra is recommended.

Название: Practical Deep Learning with PyTorch: PyTorch implementation for computer vision, NLP, audio, and language translation
Автор: Deepak Gowda
Издательство: BPB Publications
Год: 2025
Страниц: 328
Язык: английский
Формат: epub (true)
Размер: 21.2 MB

Deep Learning is revolutionizing how we solve complex problems, and PyTorch has emerged as a leading framework for its ease of use and flexibility. This book is designed to bridge the gap between theory and practice, providing a hands-on approach to understanding Deep Learning with PyTorch. It covers fundamental and advanced topics, including object detection, NLP, GANs, and time series forecasting. The book begins with foundational Deep Learning concepts and guides you through setting up PyTorch. You will learn to manipulate tensors, load data, build models, and understand computer vision with multi-object detection using YOLO to enhance image recognition through transfer learning techniques. You will also analyze generative models with GANs for data augmentation and venture into audio processing with text-to-speech and speech-to-text using TorchAudio. Learn NLP tasks like text classification, summarization, sentiment analysis, and question answering with pre-trained models like BERT. Finally, learn to tackle time series forecasting using RNNs, LSTMs, CNNs, and transformers. This book is for AI enthusiasts, data scientists, and engineers seeking practical knowledge of Deep Learning.

Название: GPT for Python-Coding in Computational Materials Science and Mechanics: From Prompt Engineering to Solutions in Worked-Out Examples
Автор: Bernhard Eidel
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2025
Страниц: 260
Язык: английский
Формат: pdf
Размер: 23.1 MB

This book covers all the topics about ChatGPT required to successfully generate Python code to solve problems in computational materials science and mechanics, complemented by numerous fully worked-out applications. The complete work flow for AI-assisted coding is given, including: (i) prompt engineering providing a powerful toolset for how to give coding assignments to ChatGPT effectively; (ii) commented code listings; and (iii) tips and tricks to verify the codes in rigorous tests including human interventions to fix issues and gaps. Finally, (iv) the coding projects are critically reviewed to address the strengths and remaining weaknesses of the Chatbot, including explicit recommendations on how to communicate with GPT. For the steps (i)–(iv) the book presents a curated selection of intriguing problems from computational materials science and computational mechanics including Machine Learning for problem-solving. These problems are carefully chosen for their relevance to current research and industrial applications and their suitability for showcasing the advanced capabilities of GPT-4 for code generation.

Название: Software Engineering Made Easy: A Comprehensive Reference Guide for Writing Good Code
Автор: Marco Gähler
Издательство: Apress
Год: 2025
Страниц: 299
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Learn how to write good code for humans. This user-friendly book is a comprehensive guide to writing clear and bug-free code. It integrates established programming principles and outlines expert-driven rules to prevent you from over-complicating your code. You’ll take a practical approach to programming, applicable to any programming language and explore useful advice and concrete examples in a concise and compact form. Sections on Single Responsibility Principle, naming, levels of abstraction, testing, logic (if/else), interfaces, and more, reinforce how to effectively write low-complexity code. While many of the principles addressed in this book are well-established, it offers you a single resource. Software Engineering Made Easy modernizes classic software programming principles with quick tips relevant to real-world applications. Intermediate programmers who have a basic understanding of coding but are relatively new to the workforce. Applicable to any programming language, but proficiency in C++ or Python is preferred. Advanced programmers may also benefit from learning how to deprogram bad habits and de-complicate their code.

Название: Comprehensive Data Structures and Algorithms in C++
Автор: Suresh Kumar Srivastava, Deepali Srivastava
Издательство: BPB Publications
Год: 2025
Страниц: 936
Язык: английский
Формат: epub (true)
Размер: 13.0 MB

Data structures and algorithms is an essential subject in computer science studies. It proves to be a great tool in the hands of any software engineer, and also plays a significant role in software design and development. It has become a must-have skill now for many competitions and job interviews in the software industry. The concepts are explained in a step-wise manner and illustrated with numerous figures, text, examples, and immediate code samples, which help in a better understanding of data structures and algorithms with their implementation. The book has more than 500 illustrations, code samples, and problems, along with solutions for exercises. This book provides practical C++ implementations and problem-solving exercises to foster a solid understanding of these core computer science concepts. After completion of this book, students will have a good understanding of data structures and algorithms concepts and implementation. Software engineers will be able to provide more effective solutions with the use of appropriate data structures and efficient algorithms.

Название: Алгоритмы вычислительной статистики в системе R
Автор: Буховец А. Г., Москалев П. В.
Издательство: Лань
Год: 2021 - 2-е изд., перераб. и доп.
Cтраниц: 160
Формат: pdf (ocr)
Размер: 27 мб
Язык: русский

В учебном пособии в краткой форме излагается теоретический материал и приводятся примеры решения практических задач по разделам: линейная алгебра, теория вероятностей, методы оценивания и проверки гипотез, метод главных компонент, регрессионный и кластерный анализ с применением свободной системы статистической обработки данных и программирования R. В приложениях к настоящему пособию содержатся сведения по установке и использованию системы R, а также листинги программ, которые могут быть использованы в учебном процессе.