Название: "Looks Good To Me": Constructive code reviews (Final Release)
Автор: Adrienne Braganza
Издательство: Manning Publications
Год: 2025
Страниц: 352
Язык: английский
Формат: epub (true)
Размер: 14.4 MB

Deliver code reviews that consistently build up your team and improve your applications. “Looks Good to Me” offers a unique approach to delivering meaningful code reviews that goes beyond superficial checklists and tense critical conversations. Instead, you’ll learn how to improve both your applications and your team dynamics. Inside “Looks Good to Me” you’ll find comprehensive coverage of every part of the code review process, from choosing a system to keeping reviews manageable for everyone involved. With this mix of tools, processes, common sense, and compassion, you’ll run a highly effective review process from first commit to final deployment. Transform code reviews into the positive, productive experiences they’re meant to be! Whether it’s your code under the microscope or you’re the one giving the feedback, this sensible guide will help you avoid the tense debates, fruitless nitpicking, and unnecessary bottlenecks you’ve come to expect from code reviews. You’ll soon be running highly effective reviews that make your code—and your team—stronger. For any team member, from developer to lead.

Название: Fixed Point Optimization Algorithms and Their Applications
Автор: Watcharaporn Cholamjiak
Издательство: Morgan Kaufmann/Elsevier
Год: 2025
Страниц: 200
Язык: английский
Формат: epub
Размер: 37.2 MB

Fixed Point Optimization Algorithms and Their Applications discusses how the relationship between fixed point algorithms and optimization problems is connected and demonstrates hands-on applications of the algorithms in fields such as image restoration, signal recovery, and machine learning. The author presents algorithms for non-expansive and generalized non-expansive mappings in Hilbert space, and includes solutions to many optimization problems across a range of scientific research and real-world applications. From foundational concepts, the book proceeds to present a variety of optimization algorithms, including fixed point theories, convergence theorems, variational inequality problems, minimization problems, split feasibility problems, variational inclusion problems, and equilibrium problems. This book will equip readers with the theoretical mathematics background and necessary tools to tackle challenging optimization problems involving a range of algebraic methods, empowering them to apply these techniques in their research, professional work, or academic pursuits.

Название: Linux Coding Tricks & Tips - 20th Edition, 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 41.3 MB

"Linux Coding Tricks & Tips" - это идеальное цифровое руководство для тех читателей, которые желают поднять свои навыки программирования на более высокий уровень. Вы хотите улучшить свой пользовательский опыт или получить инсайдерские знания? Вы хотите учиться непосредственно у экспертов в этой области? Хотите узнать бесчисленные шорткаты, которыми пользуются профессионалы? На страницах этого нового издания для продвинутых пользователей вы узнаете все, что нужно, чтобы стать более уверенным, знающим и опытным пользователем. Пользователем, который получит максимальную отдачу от программирования на Python и C++, а значит, и от самого Linux.

Название: Машинное обучение с использованием библиотеки Н2О
Автор: Кук Д.
Издательство: ДМK
Год: 2018
Cтраниц: 250
Формат: pdf (ocr)
Размер: 41 мб
Язык: русский

Н2О – простая в использовании и открытая библиотека, которая поддерживает большое количество операционных систем и языков программирования, а также масштабируется для обработки больших данных. Эта книга научит вас использовать алгоритмы машинного обучения, реализованные в Н2О, с упором на наиболее важные для продуктивной работы аспекты.

Название: Программирование искусственного интеллекта в приложениях
Автор: Джонс М.Т.
Издательство: ДМK
Год: 2011
Cтраниц: 312
Формат: pdf (ocr)
Размер: 38 мб
Язык: русский

Данная книга посвящена вопросам искусственного интеллекта (ИИ), то есть методам и технологиям, призванным сделать ПО более умным и полезным. Рассмотренные алгоритмы в основном предназначены для встраивания в другое программное обеспечение, что позволяет создавать программы, гибко подстраивающиеся под требования и привычки пользователя.

Название: How to Think about Algorithms, 2nd Edition
Автор: Jeff Edmonds
Издательство: Cambridge University Press
Год: 2024
Страниц: 618
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Understand algorithms and their design with this revised student-friendly textbook. Unlike other algorithms books, this one is approachable, the methods it explains are straightforward, and the insights it provides are numerous and valuable. Without grinding through lots of formal proof, students will benefit from step-by-step methods for developing algorithms, expert guidance on common pitfalls, and an appreciation of the bigger picture. Revised and updated, this second edition includes a new chapter on Machine Learning algorithms, and concise key concept summaries at the end of each part for quick reference. Also new to this edition are more than 150 new exercises: selected solutions are included to let students check their progress, while a full solutions manual is available online for instructors. No other text explains complex topics such as loop invariants as clearly, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.

Название: Python All-in-One For Dummies, 3rd Edition
Автор: John Shovic, Alan Simpson
Издательство: For Dummies
Год: 2024
Страниц: 706
Язык: английский
Формат: True/Retail PDF
Размер: 42.2 MB

Everything you need to know to get into Python coding, with 7 books in one. Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. This book is a reference manual to guide you through the process of learning Python and how to use it in modern computer applications, such as data science, artificial intelligence, physical computing, and robotics. If you're looking to learn a little about a lot of exciting things, this is the book for you. It gives you an introduction to the topics that you'll need to explore more deeply. Python All-in-One For Dummies, 3rd Edition guides you through the Python language and then takes you on a tour through some cool libraries and technologies (the Raspberry Pi, robotics, AI, Data Science, and more) that all revolve around the Python language. When you work on new projects and new technologies, Python is there with a diverse number of libraries just waiting for you to use.

Название: Geocomputation with Python
Автор: Michael Dorman, Anita Graser, Jakub Nowosad, Robin Lovelace
Издательство: CRC Press
Серия: The Python Series
Год: 2025
Страниц: 309
Язык: английский
Формат: pdf (true), epub
Размер: 37.4 MB

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world. The book gives an overview of Python's capabilities for spatial data analysis, as well as dozens of worked-through examples covering the entire range of standard GIS operations. A unique selling point of the book is its cohesive and joined-up coverage of both vector and raster geographic data models and consistent learning curve. This book is an excellent starting point for those new to working with geographic data with Python, making it ideal for students and practitioners beginning their journey with Python. The book teaches how to import, process, examine, transform, compute, and export spatial vector and raster datasets with Python, the most widely used language for Data Science and many other domains. Reading the book and running the reproducible code chunks within will make you a proficient user of key packages in the ecosystem, including shapely, geopandas, and rasterio.

Название: Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning
Автор: Iacovos Ioannou, Vasos Vassiliou, Prabagarane Nagaradjane, Christophoros Christophorou
Издательство: CRC Press
Год: 2025
Страниц: 261
Язык: английский
Формат: pdf (true), epub
Размер: 16.6 MB

The aim of this book is to delineate the challenges faced by new generation mobile networks, such as 5G and forthcoming 6G, and introduce the concept of addressing these challenges through the development of a novel Distributed AI (DAI) framework. The book proposes a distributed AI approach to handle these complexities effectively. Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning aims to provide a comprehensive understanding of the proposed DAI framework, its architecture, implementation, and application in the context of D2D communication in 5G and beyond networks. It showcases how the framework can enhance decision-making, control, and communication performance while considering both static and dynamic network environments. This book is intended for professionals that specialize in designing, implementing, and maintaining communication networks such as telecommunications/ communication engineers, wireless engineers. The book's emphasis on incorporating AI and ML techniques in the proposed framework also makes it of interest to computer and software engineers working in Artificial Intelligence and Machine Learning engineers.

Название: Software Vulnerability Discovery Process: Concepts and Applications
Автор: Adarsh Anand, Navneet Bhatt, Omar H Alhazmi
Издательство: River Publishers
Год: 2025
Страниц: 151
Язык: английский
Формат: pdf (true), epub
Размер: 15.3 MB

This book is an overview of basics and other related fundamentals pertaining to software vulnerability discovery as a process. This collaboration of academia and industry disseminates various practical mathematical modeling-based tools and analytics used for vulnerability discovery. This book is designed to understand the use of basic fundamentals, various mathematical models, and approaches that illustrate the analytical reasoning and modeling that can provide an in-depth understanding of the thin line of difference and that minute connectivity of the software vulnerability models with the already available concepts of software reliability growth modeling. In the chapters, focus has been on to explain the concepts utilized by various researchers so as to understand the software vulnerability discovery process from a conceptual framework. Some chapters also carry the numerical illustration part to showcase the application of the discussed models.