Litgu.ru - Литературный Гуру

Название: PowerShell 101: The No-Nonsense Beginner's Guide to PowerShell
Автор: Mike F. Robbins
Издательство: Leanpub
Год: 2023-07-19
Страниц: 160
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Before PowerShell, I spent the first third of my career as an IT Pro pointing and clicking in the GUI and I decided to write this book to save IT Pros from themselves who are reluctant to learn PowerShell. Instead of a book that just covers topics with fictitious scenarios, this book is more of a condensed version targeting the specific topics that I’ve found an IT Pro needs to know initially to be successful with PowerShell in a real world production environment. It’s a collection of what I wish someone would have told me when I started learning PowerShell along with the tips, tricks, and best practices that I've learned while using PowerShell during the past 10 years. This book focuses on PowerShell version 5.1 in a Microsoft Active Directory domain environment running on Windows 10 and Windows Server 2016. All currently supported versions of Windows and previous versions of PowerShell beginning with PowerShell version 1.0 are briefly mentioned in this book.

Название: Functional Design and Architecture (MEAP v10)
Автор: Alexander Granin
Издательство: Manning Publications
Год: 2023
Страниц: 559
Язык: английский
Формат: pdf, epub
Размер: 18.4 MB

Design patterns and architectures for building production quality applications using functional programming, with examples in Haskell and other FP languages. Functional Design and Architecture is a pioneering guide to software engineering using Haskell and other functional languages. In it, you’ll discover Functional Declarative Design and other design principles perfect for working in Haskell, PureScript, F#, and Scala. Functional programming offers a powerful alternative to object-oriented programming that helps tackle the complexities of large-scale software. Entrenched design patterns and architectural principles made for OOP are poorly suited for creating large-scale functional applications. This book lays out new methodologies, principles, and architectures optimized for high-level software design using functional languages. Inside, you’ll find cutting-edge functional design principles and practices for every stage of application development, from architecting your application through to running simple and maintainable tests. There’s no abstract theory—you’ll learn by building exciting sample applications, including an application for controlling a spaceship and a full-fledged backend framework.

Название: Linear Algebra And Optimization With Applications To Machine Learning - Volume II: Fundamentals of Optimization Theory with Applications to Machine Learning
Автор: Jean Gallier, Jocelyn Quaintance
Издательство: World Scientific Publishing
Год: 2021
Страниц: 896
Язык: английский
Формат: pdf (true)
Размер: 22.2 MB

Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout Machine Learning. This book blends theory with practice by not only carefully discussing the mathematical under pinnings of each optimization technique but by applying these techniques to linear programming, support vector machines (SVM), principal component analysis (PCA), and ridge regression. Volume 2 begins by discussing preliminary concepts of optimization theory such as metric spaces, derivatives, and the Lagrange multiplier technique for finding extrema of real valued functions. The focus then shifts to the special case of optimizing a linear function over a region determined by affine constraints, namely linear programming. Highlights include careful derivations and applications of the simplex algorithm, the dual-simplex algorithm, and the primal-dual algorithm. The theoretical heart of this book is the mathematically rigorous presentation of various nonlinear optimization methods, including but not limited to gradient decent, the Karush-Kuhn-Tucker (KKT) conditions, Lagrangian duality, alternating direction method of multipliers (ADMM), and the kernel method. These methods are carefully applied to hard margin SVM, soft margin SVM, kernel PCA, ridge regression, lasso regression, and elastic-net regression. Matlab programs implementing these methods are included.

Название: Embedded Software System Testing: Automatic Testing Solution Based on Formal Method
Автор: Yongfeng Yin, Bo Jiang
Издательство: CRC Press
Год: 2024
Страниц: 330
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book introduces embedded software engineering and management methods, proposing the relevant testing theory and techniques that promise the final realization of automated testing of embedded systems. The quality and reliability of embedded systems have become a great concern, faced with the rising demands for the complexity and scale of system hardware and software. The authors propose and expound on the testing theory and techniques of embedded software systems and relevant environment construction technologies, providing effective solutions for the automated testing of embedded systems. Through analyzing typical testing examples of the complex embedded software systems, the authors verify the effectiveness of the theories, technologies and methods proposed in the book. In combining the fundamental theory and technology and practical solutions, this book will appeal to researchers and students studying computer science, software engineering, and embedded systems, as well as professionals and practitioners engaged in the development, verification, and maintenance of embedded systems in the military and civilian fields.

Название: Learn OpenCV with Python by Examples: Implement Computer Vision Algorithms Provided by OpenCV with Python for Image Processing, Object Detection and Machine Learning 2nd Edition
Автор: James Chen
Издательство: Independently published
Год: 2023
Страниц: 316
Язык: английский
Формат: epub (true)
Размер: 35.4 MB

This book is a comprehensive guide to learning the basics of computer vision and Machine Learning using the powerful OpenCV library and the Python programming language. The book offers a practical, hands-on approach to learning the concepts and techniques of computer vision through practical examples. All codes in this book are available on Github. Through a series of examples, the book covers a wide range of topics including image and video processing, feature detection, object detection and recognition, machine learning, and deep neural networks. Each chapter includes detailed explanations of the concepts and techniques involved, as well as practical examples and code snippets that demonstrate how to implement them in Python. Throughout the book, readers will work through hands-on examples and projects, learning how to build image-processing applications from scratch. Whether you are a beginner or an experienced programmer, this book provides a valuable resource for learning computer vision with OpenCV and Python. The clear and concise writing style makes it easy for readers to follow along, and the numerous examples ensure that readers can practice and apply what they have learned. By the end of the book, readers will have a solid understanding of the fundamentals of computer vision and be able to build their own computer vision applications with confidence.

Название: Essentials of Software Testing
Автор: Ralf Bierig, Stephen Brown, Edgar Galván
Издательство: Cambridge University Press
Год: 2022
Страниц: 324
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Software testing can be regarded as an art, a craft, and a science. The practical, step-by-step approach presented in this book provides a bridge between these different viewpoints. A single worked example runs throughout, with consistent use of test automation. Each testing technique is introduced in the context of this example, helping students see its strengths and weaknesses. The technique is then explained in more detail, providing a deeper understanding of underlying principles. Finally the limitations of each technique are demonstrated by inserting faults, giving learners concrete examples of when each technique succeeds or fails in finding faults. Coverage includes black-box testing, white-box testing, random testing, unit testing, object-oriented testing, and application testing. The authors also emphasise the process of applying the techniques, covering the steps of analysis, test design, test implementation, and interpretation of results. The book's web site has programming exercises and Java source code for all examples.

Название: Cryptocurrency Price Analysis, Prediction, And Forecasting Using Machine Learning With Python, Second Edition
Автор: Vivian Siahaan, Rismon Sianipar
Издательство: Balige Publishing
Год: July 2023
Страниц: 401
Язык: английский
Формат: epub (true)
Размер: 17.5 MB

In this project, we will be conducting a comprehensive analysis, prediction, and forecasting of cryptocurrency prices using machine learning with Python. The dataset we will be working with contains historical cryptocurrency price data, and our main objective is to build models that can accurately predict future price movements and daily returns. The first step of the project involves exploring the dataset to gain insights into the structure and contents of the data. We will examine the columns, data types, and any missing values present. After that, we will preprocess the data, handling any missing values and converting data types as needed. This will ensure that our data is clean and ready for analysis. Next, we will proceed with visualizing the dataset to understand the trends and patterns in cryptocurrency prices over time. We will create line plots, box plot, violin plot, and other visualizations to study price movements, trading volumes, and volatility across different cryptocurrencies. As part of our Machine Learning efforts, we will also develop models for predicting daily returns of cryptocurrencies. Daily returns are essential indicators for investors and traders, as they reflect the percentage change in price from one day to the next.

Название: Основы разработки приложений беспроводных устройств
Автор: Котляров В.П., Воинов Н.В.
Издательство: М.: НОУ "Интуит"
Год: 2016
Страниц: 328
Формат: PDF
Размер: 24.6 Мб
Язык: русский

Курс посвящен обсуждению проблем разработки программного обеспечения приложений беспроводных устройств. В этой области наряду с решением научных и технических проблем немаловажная роль принадлежит проблеме подготовки кадров, пригодных к решению задач создания приложений для мобильных телефонов, смартфонов, наладонников, ноутбуков, взаимодействующих в распределенной сети.

Название: Программирование на ASP.NET
Автор: Снетков В.М.
Издательство: М.: НОУ "Интуит"
Год: 2016
Страниц: 901
Формат: PDF
Размер: 105 Мб
Язык: русский

Курс посвящен технологии программирования web-приложений на ASP.NET с использованием Visual Studio 2005. В курсе подробно рассказывается об этапах создания web-сайтов, программировании форм, серверных и пользовательских элементах управления. Рассказывается о средствах форматирования страниц, технологии ADO.NET, работе с файлами и каталогами и управлении безопасностью сайта.

Название: Machine Learning System Design: With end-to-end examples (MEAP v4)
Автор: Arseny Kravchenko, Valerii Babushkin
Издательство: Manning Publications
Год: 2023
Страниц: 207
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Get the big picture and the important details with this end-to-end guide for designing highly effective, reliable Machine Learning systems. Machine Learning System Design: With end-to-end examples is a practical guide for planning and designing successful ML applications. It lays out a clear, repeatable framework for building, maintaining, and improving systems at any scale. Authors Arseny Kravchenko and Valeri Babushkin have filled this unique handbook with campfire stories and personal tips from their own extensive careers. You’ll learn directly from their experience as you consider every facet of a machine learning system, from requirements gathering and data sourcing to deployment and management of the finished system. Machine Learning system design is complex. The successful ML engineer needs to navigate a multistep process that demands skills from many different fields and roles. This one-of-kind-guide starts by showing you the big picture and then guides you step by step through a framework for creating successful systems. You’ll learn to excel at delivering for global objectives, diving locally into tools, and combining your knowledge into an integrated vision. For readers who know the basics of both software engineering and machine learning. Examples in Python.