Название: Collaborative Software Design (MEAP v6)
Автор: Evelyn van Kelle
Издательство: Manning Publications
Год: 2023
Страниц: 431
Язык: английский
Формат: pdf, epub
Размер: 45.9 MB

Good practices, collaboration tools, and effective techniques for incorporating your key stakeholders into the software design process. Don’t spend months building the wrong software! Collaborative Software Design: How to facilitate domain modeling decisions is a unique and practical guide for effectively involving all stakeholders in the design of software. Collaborative Software Design: How to facilitate domain modeling decisions is a practical guide to conducting effective software design sessions that involve all business and technical stakeholders. It lays out pragmatic techniques for making collaborative design decisions, ensuring you’re getting a group’s full participation and input to solve real business problems. You’ll deliver results by combining collaborative modeling tools, and learn how to manage conflicts, handle resistance, and keep everyone involved even when a session has ended. Put these techniques into practice, and you’ll be able to facilitate incredibly effective design sessions in which everyone’s voices are heard.

Название: The AI-Powered Developer (MEAP v1)
Автор: Nathan B Crocker
Издательство: Manning Publications
Год: 2023
Страниц: 134
Язык: английский
Формат: pdf, epub
Размер: 10.5 MB

Use groundbreaking generative AI tools to increase your productivity, efficiency, and code quality. You just got a promotion! AI coding tools like GitHub Copilot, ChatGPT, and Amazon CodeWhisperer turn every developer into an engineering manager, overseeing a super-smart and super-fast junior coder. This book is designed to transition readers from having little to no experience with AI-powered coding tools to becoming proficient developers able to leverage these powerful technologies in their projects. Given the broadness of introducing both programming and AI concepts, we assume you're familiar with Python. The AI-Powered Developer shows you how to put AI coding tools like Github Copilot and ChatGPT into action. Throughout the book, you’ll generate code and design ideas as you build an IT Asset Management system using AI in every step of the development process. Clear advice and hands-on examples show you how to integrate these tools into your daily workflow. You’ll create self-documenting applications, generate predictive suggestions, and even use AI to test and explain your code. This practical book helps you develop an instinct for AI code and an understanding of what problems AI can and can’t solve. You’ll soon be confident in your transition to this new way to build software, aided by your diligent team of AI assistants.

Название: Путешествие в страну Алгоритмию с котенком Скретчем
Автор: Зорина Е.М.
Издательство: ДМK
Год: 2016
Cтраниц: 134, цвет.ил.
Формат: pdf (ocr)
Размер: 14 мб
Язык: русский

Давай вместе отправимся в удивительный мир программирования – страну Алгоритмию, где ты сможешь помочь котенку Scratch спасти Инфоград от злобного Вируса. Ты научишься создавать игры и анимации, которыми сможешь поделиться с друзьями. Программировать – это интересно. А программировать игры – вдвойне!

Название: Conquering jаvascript: Node.js
Автор: Sufyan bin Uzayr
Издательство: CRC Press
Год: 2024
Страниц: 188
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

jаvascript is without a question among the most prominent and commonly used client-side programming languages available. jаvascript's scope of use has expanded in recent years, and it is now also used for server-side development. Node.js is an extremely popular JS framework, meant for rapid web and application development. Conquering jаvascript: Node.js helps the reader master the Node.js framework for faster and more robust development. This book is a detailed guide that will help developers and coders do more with Node.js. It discusses the basics in brief, and then moves on to more advanced and detailed exercises to help readers quickly gain the required knowledge. This book is a valuable reference for Node.js developers as well as those involved in game development, mobile apps, progressive applications, and now even desktop apps.

Название: Mastering Perl: A Beginner's Guide
Автор: Sufyan bin Uzayr
Издательство: CRC Press
Год: 2024
Страниц: 313
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Mastering Perl helps readers to learn the Perl programming language with real-world examples. High-level, interpreted, and multipurpose, Perl’s roots are in text manipulation. It is used for UI development in system administration, networking, and other fields, borrowing heavily from C and Shell scripts. Among programmers, Perl is also known as "Pathologically Eclectic Rubbish Lister" or "Practically Everything Really Likable." Since Perl’s inception, it has mostly been used for text processing, namely the extraction of data from text files and its subsequent transformation into other formats. In addition to being interoperable with HTML, XML, and other markup languages, Perl provides cross-platform compatibility. It is Open Source, meaning it is free to use and licensed under both the Artistic and GNU General Public Licenses (GPL).

Название: Quick Java
Автор: David Matuszek
Издательство: CRC Press
Год: 2024
Страниц: 235
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

"We’ll be doing this next project in Java." Unfortunately, you’re a C++ programmer, or maybe a Python programmer. How are you going to get up to speed in a hurry? There are lots of Java books for beginners, telling you all about what a computer is and how it represents everything in bits. You don’t need that. At the other extreme, there are thousand-page tomes that you aren’t going to get through in a few days, if ever. You need something in-between. This book is intended to fill that gap. It’s written for the programmer who doesn’t need to be taught how to program, just how to do it in Java―and who needs to get started in a hurry. Java is covered from the inside out. First, all the things that go inside a class, most of which are practically identical to C++. After that, all the various and complicated kinds of classes and interfaces and how they relate to each other in large-scale programs. Testing is essential, so (unlike most Java books) JUnit is covered in detail. Then, in case you need to go in that direction, some functional programming, a little about parallel programming, and more than enough to get you started in building GUIs (graphical user interfaces) and doing animation.

Название: Making "Hidden Objects" Browser Games: Creating "Find-the-Difference" Game Mechanics for Phaser.js Gaming Frameworks v3.x.x & v2.x.x
Автор: Stephen Gose
Издательство: Leanpub
Год: 2021-12-02
Страниц: 163
Язык: английский
Формат: pdf (true), epub
Размер: 12.0 MB

This workbook is intended to be a hands-on guide for HTML5 front-end game development with an emphasis on the Phaser jаvascript Gaming Framework — either v2.x.x or III. Yet, our game product and project management could apply to any game development framework! It’s not exclusive to the Phaser JS Gaming Framework. Expert game developers understand the “Don’t Repeat Yourself” (D.R.Y.) concept, yet few have taken a step back to the “10,000-foot view” on their game production pipelines. We’ll do that aerial view in this book as we follow this game’s development process and then “nose dive head-first” directly into Phaser Gaming Framework v2.x.x and III. I believe you will be surprised how quickly and easily we can build games using this Game Design System™ with its Game Recipes tools. This book will not teach you HTML5, CSS nor jаvascript programming fundamentals, game design allegedly “best practices”, nor software encoding syntax. (see Appendix: “JS OLOO for Modern Game Development Method”) I assume you (the reader) already knows these technologies. This workbook does provide simple-to-follow worksheets, step-by-step instructions, and a straightforward approach to building a specific game genre from component prototypes using the Game Design System methods discussed in the Headless HTML5 Game Design, Phaser Game Design, and Phaser Game Prototyping Workbooks.

Название: Machine Learning For Concrete Compressive Strength Analysis And Prediction With Python, Second Edition
Автор: Vivian Siahaan, Rismon Sianipar
Издательство: Balige Publishing
Год: July 2023
Страниц: 245
Язык: английский
Формат: epub (true)
Размер: 19.7 MB

Welcome to "Machine Learning for Concrete Compressive Strength Analysis and Prediction with Python." In this book, we will explore the fascinating field of applying machine learning techniques to analyze and predict the compressive strength of concrete. First, we will dive into the dataset, which includes various features related to concrete mix proportions, age, and other influential factors. We will explore the dataset's structure, dimensions, and feature types, ensuring that we have a solid understanding of the data we are working with. Then, we will focus on data exploration and visualization. We will utilize histograms, box plots, and scatter plots to gain insights into the distribution of features and their relationships with the target variable, enabling us to uncover valuable patterns and trends within the dataset. Before delving into machine learning algorithms, we must preprocess the data. We will handle missing values, encode categorical variables, and scale numerical features to ensure that our data is in the optimal format for training and testing our models. Then, we will explore popular algorithms such as Linear Regression, Decision Trees, Random Forests, Support Vector, Naïve Bayes, K-Nearest Neighbors, Adaboost, Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting, Catboost, and Multi-Layer Perceptron regression algorithms and use them to predict the concrete compressive strength accurately.

Название: Time-Series Weather: Forecasting And Prediction With Python
Автор: Vivian Siahaan, Rismon Sianipar
Издательство: Balige Publishing
Год: July 2023
Страниц: 246
Язык: английский
Формат: epub (true)
Размер: 15.8 MB

In this project, we embarked on a journey of exploring time-series weather data and performing forecasting and prediction using Python. The objective was to gain insights into the dataset, visualize feature distributions, analyze year-wise and month-wise patterns, apply ARIMA regression to forecast temperature, and utilize machine learning models to predict weather conditions. Let's delve into each step of the process. To begin, we started by exploring the dataset, which contained historical weather data. We examined the structure and content of the dataset to understand its variables, such as temperature, humidity, wind speed, and weather conditions. Understanding the dataset is crucial for effective analysis and modeling. Next, we visualized the distributions of different features. By creating histograms, box plots, and density plots, we gained insights into the range, central tendency, and variability of the variables. These visualizations allowed us to identify any outliers, skewed distributions, or patterns within the data. In conclusion, this project demonstrated the power of Python in time-series weather forecasting and prediction. Through data exploration, visualization, regression analysis, and Machine Learning modeling, we obtained valuable insights and accurate predictions regarding temperature and weather conditions. This knowledge can be applied in various domains such as agriculture, transportation, and urban planning, enabling better decision-making based on weather forecasts.

Название: Default Loan Prediction Based On Customer Behavior Using Machine Learning And Deep Learning With Python, Second Edition
Автор: Vivian Siahaan, Rismon Sianipar
Издательство: Balige Publishing
Год: July 2023
Страниц: 337
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

In this project, we aim to predict the risk of defaulting on a loan based on customer behavior using Machine Learning and Deep Learning techniques. We start by exploring the dataset and understanding its structure and contents. The dataset contains various features related to customer behavior, such as credit history, income, employment status, loan amount, and more. We analyze the distribution of these features to gain insights into their characteristics and potential impact on loan default. Next, we preprocess the data by handling missing values, encoding categorical variables, and normalizing numerical features. This ensures that the data is in a suitable format for training Machine Learning models. After evaluating the performance of these Machine Learning models, we turn our attention to Deep Learning techniques. We design and train an Artificial Neural Network (ANN) to predict the risk flag for loan default. The ANN consists of multiple layers of interconnected neurons that learn hierarchical representations of the input features.