Название: Image Processing and Machine Learning, Volume 1: Foundations of Image Processing
Автор: Erik Cuevas, Alma Nayeli Rodríguez
Издательство: CRC Press
Год: 2024
Страниц: 225
Язык: английский
Формат: pdf (true)
Размер: 40.9 MB

Image processing and Machine Learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, Machine Learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. Our primary objective was to create a comprehensive textbook that serves as an invaluable resource for an image processing class. With this goal in mind, we carefully crafted a book that encompasses both the theoretical foundations and practical applications of the most prevalent image processing methods. From pixel operations to geometric transformations, spatial filtering to image segmentation, and edge detection to color image processing, we have meticulously covered a wide range of topics essential to understanding and working with images. Moreover, recognizing the increasing relevance of ML in image processing, we have incorporated fundamental ML concepts and their applications in this field. By introducing readers to these concepts, we aim to equip them with the necessary knowledge to leverage ML techniques for various image processing tasks. Volume 1 is organized in a way that allows readers to easily understand the goal of each chapter and reinforce their understanding through practical exercises using MATLAB programs.

Название: Image Processing and Machine Learning, Volume 2: Advanced Topics in Image Analysis and Machine Learning
Автор: Erik Cuevas, Alma Nayeli Rodríguez
Издательство: CRC Press
Год: 2024
Страниц: 239
Язык: английский
Формат: pdf (true)
Размер: 31.6 MB

Image processing and Machine Learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, Machine Learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important Machine Learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1. Machine Learning (ML) is a branch of artificial intelligence (AI) that enables systems to learn from data and make informed predictions or decisions without the need for explicit programming. ML finds extensive applications in various domains. For instance, in automation, ML algorithms can automate tasks that would otherwise rely on human intervention, thereby reducing errors and enhancing overall efficiency. Predictive analytics is another area where ML plays a crucial role. By analyzing vast datasets, ML models can detect patterns and make predictions, facilitating applications such as stock market analysis, fraud detection, and customer behavior analysis. We have observed that students grasp the material more effectively when they have access to code that they can manipulate and experiment with. In line with this, our book utilizes MATLAB as the programming language for implementing the systems.

Название: Unity. Полное руководство
Автор: Корнилов А.В.
Издательство: СПб.: Наука и техника
Год: 2021
Формат: pdf
Страниц: 496
Размер: 79 mb
Язык: Русский

В этой книге мы расскажем, как с использованием Unity (популярной меж­платформенной среды разработки компьютерных игр) вы сможете САМИ создавать свои игры и трехмерные миры, причем без лишних затрат и про­фессиональных навыков программирования.
Книга поделена на три части. Первая часть посвящена изучению интерфейса и основных возможностей Unity. Мы поговорим о двух- и трехмерных проек­тах; рассмотрим ключевые особенности Unity; узнаем, как использовать ассе­ты; подробном изучим интерфейс Unity; узнаем об игровых объектах, сценах, камерах, источниках света; создадим свои первые Unitу-проекты.

Название: Расширенная аналитика с PySpark: Практические примеры анализа больших наборов данных с использованием Python и Spark
Автор: Акаш Тандон, Сэнди Райза, Ури Ласерсон
Издательство: БХВ-Петербург
Год: 2023
Страниц: 226
Язык: русский
Формат: pdf, djvu
Размер: 36.3 MB

Книга посвящена практическим методам анализа больших объемов данных с использованием языка Python и фреймворка Spark, она знакомит с моделью программирования Spark и основами системы с открытым исходным кодом PySpark. Каждая глава описывает отдельный аспект анализа данных, показаны основы обработки данных в PySpark и Python на примере очистки данных, подробно освещается машинное обучение с помощью Spark. Книга поможет читателю понять, как устроен и работает весь конвейер PySpark для комплексной аналитики больших наборов данных: от создания и оценки моделей до очистки, предварительной обработки и исследования данных с особым акцентом на производственные приложения. Отдельные главы посвящены обработке изображений и библиотеке Spark NLP. Эта книга не рассказывает о достоинствах и недостатках PySpark. Книга знакомит с моделью программирования Spark и основами PySpark — API Python для Spark. Тем не менее она не претендует на то, чтобы служить справочником по Spark или быть исчерпывающим путеводителем по всем закоулкам Spark. Она также не претендует на роль справочника по машинному обучению, статистике или линейной алгебре, хотя во многих главах содержится небольшой вводный материал перед их использованием. Эта книга поможет читателю понять, как устроен и работает весь конвейер PySpark для комплексной аналитики больших наборов данных, а это не только создание и оценка моделей, но также очистка, предварительная обработка и исследование данных с особым акцентом на производственные приложения.

Название: Библиотека программирования на Python. Сборник (180 книг)
Автор(ы): разные
Издательство: Москва
Год: 2001-2024
Страниц: 1000+
Формат: pdf
Размер: 4 Гб
Язык: русский

Сборник книг "Библиотека программирования на Python" предназначен как для опытных мастеров своего дела, так и для тех, кто только приступил к изучению программирования. В данном выпуске библиотеки книги, посвященные изучению Python.

Название: Learn Programming with C An Easy Step-by-Step Self-Practice Book for Learning C
Автор: Sazzad M.S. Imran, Atiqur Rahman Ahad
Издательство: CRC Press
Год: 2024
Страниц: 580
Язык: английский
Формат: pdf (true)
Размер: 22.6 MB

Authored by two standout professors in the field of Computer Science and Technology with extensive experience in instructing, Learn Programming with C: An Easy Step-by Step Self-Practice Book for Learning C is a comprehensive and accessible guide to programming with one of the most popular languages. Meticulously illustrated with figures and examples, this book is a comprehensive guide to writing, editing, and executing C programs on different operating systems and platforms, as well as how to embed C programs into other applications and how to create one’s own library. A variety of questions and exercises are included in each chapter to test the readers’ knowledge. Written for the novice C programmer, especially undergraduate and graduate students, this book’s line-by-line explanation of code and succinct writing style makes it an excellent companion for classroom teaching, learning, and programming labs. C is a programming language with which every software developer should become familiar. Though numerous books are available on C programming language, most of the example programs are written without algorithms or any flowchart in those books. As a result, it becomes difficult for a student to comprehend the core of a programming language through a self-learning approach. Our experience in teaching C underscores the importance of presenting C programs by the flowchart solution first, then the pseudocode solution, and finally the actual C code with the line-by-line explanation. It is written for C programming language courses/modules at the undergraduate and graduate levels - mostly for beginners.

Название: Mastering TypeScript: A Comprehensive Guide to Learn TypeScript Programming
Автор: Cybellium Ltd
Издательство: Cybellium Ltd
Год: 2023
Страниц: 314
Язык: английский
Формат: epub
Размер: 10.2 MB

Shaping the Frontier of Web Development. Delve into the dynamic world of TypeScript—a powerful superset of jаvascript, designed to enhance productivity, facilitate large-scale applications, and push web development boundaries. Whether you're a frontend enthusiast, a backend guru, or someone in-between, "Mastering TypeScript" stands as your comprehensive companion in this journey. TypeScript is an open-source programming language that was developed and is maintained by Microsoft. The primary objective of TypeScript is to extend the capabilities of jаvascript by adding static types. The significance of this can be best understood when we compare it to jаvascript, a dynamically typed language. jаvascript, since its inception, has been one of the most popular programming languages for web development. However, as applications grow larger and more complex, certain limitations inherent to jаvascript become apparent. jаvascript being a dynamically typed language means that variable types are checked at runtime, and this lack of type safety can lead to runtime errors that are hard to track down and debug. TypeScript addresses this challenge by introducing static types. Static types allow developers to annotate their code with type information, which is then used by the TypeScript compiler for type checking at compile-time rather than runtime. This early error detection helps developers catch and fix errors more efficiently, resulting in more robust, reliable code.

Название: Handbook of Artificial Intelligence Applications for Industrial Sustainability: Concepts and Practical Examples
Автор: Vikas Garg, Richa Goel, Pooja Tiwari
Издательство: CRC Press
Год: 2024
Страниц: 325
Язык: английский
Формат: pdf (true)
Размер: 35.6 MB

The subject of Artificial Intelligence (AI) is continuing on its journey of affecting each and every individual and will keep on this path in the times to come. This handbook is a collection of topics on the application of artificial intelligence applications for sustainability in different areas. It provides an insight into the various uses of concepts and practical examples for different domains all in one place, which makes it unique and important for the potential reader. Handbook of Artificial Intelligence Applications for Industrial Sustainability: Concepts and Practical Examples examines the influence of AI and how it can be used in several industries to improve corporate performance, reduce security concerns, improve customer experience, and ultimately generate value for customers and maximize profits. The handbook offers practical examples, concepts, and applications that provide an easy understanding and implementation process. Covering topics that include examination of Artificial Intelligence applications of enterprises in terms of sustainability in the marketing, sustainable green fashion industry, e-​commerce industry, banking services, HRM, Artificial Intelligence models in pattern recognition, concepts challenges and applications, agricultural sector, sustainable education, workforce analytics, talent management, fraud detection, cyber security will have the potential to contribute to sustainability in two ways: directly by making certain processes more sustainable, and indirectly by encouraging people to live more environmentally friendly lives. This handbook will provide insight to customers, managers, professionals, engineers, researchers, and students on the various uses of AI and sustainability in different domains. All of this needed information compiled into one handbook makes it unique and important for the engineering, business, and Computer Science communities.

Название: Game AI Uncovered: Volume One
Автор: Paul Roberts
Издательство: CRC Press
Год: 2024
Страниц: 217
Язык: английский
Формат: pdf (true)
Размер: 19.2 MB

Game AI Uncovered: Volume One kicks off a brand-new series of books that focus on the development of artificial intelligence in video games. This volume brings together the collected wisdom, ideas, tricks, and cutting-edge techniques from 20 of the top game AI professionals and researchers from around the world. The techniques discussed in these pages cover the underlying development of a wide array of published titles, including Hood: Outlaws and Legends, The Escapists 2, Sackboy: A Big Adventure, Call of Duty: Strike Team, GTI+ Club, Split/Second, Sonic All Stars Racing Transformed, Luna Abyss, Medal of Honor Heroes I & II, Age of Empires IV, Watch Dogs, Battlefield 2042, Plants vs. Zombies: Battle for Neighborville, Dead Space, and more. Contained within this volume are overviews and insight covering a host of different areas within game AI, including situational awareness, pathfinding, tethering, squad behaviours, coordination, auto-generating navigation link data, fluid movement, combining behaviour and animation systems, pedal control for cars, tactical positioning, level of detail, infinite axis utility systems, hierarchical state machines, bots for testing, reactive behaviour trees, and more. For me, Game Artificial Intelligence is by far the most interesting part of game development. That is not to disparage the great work that is done in graphics, physics, tools, audio, and all the other vital components required to make a game, but there is something special about bringing an agent to life. It is not only about the end result though, but also about how you get there. The smoke and mirrors that are used for a player to buy into the illusion and keep them there. Beginners to the area of game AI, along with professional developers, will find a wealth of knowledge that will not only help in the development of your own games but will also spark ideas for new approaches.

Название: Intermediate Quantitative Economics with Python
Автор: Thomas J. Sargent, John Stachurski
Издательство: QuantEcon
Год: Dec 21, 2023
Страниц: 1481
Язык: английский
Формат: pdf (true)
Размер: 27.2 MB

This book presents a set of lectures on Python programming for economics and finance. Substantial parts of Machine Learning and Artificial Intelligence are аbout: • approximating an unknown function with a known function; • estimating the known function from a set of data on the left- and right-hand variables. This lecture describes the structure of a plain vanilla Artificial Neural Network (ANN) of a type that is widely used to approximate a function f that maps x in a space X into y in a space Y. To introduce elementary concepts, we study an example in which x and y are scalars. We’ll describe the following concepts that are brick and mortar for neural networks: • a neuron; • an activation function; • a network of neurons; • A neural network as a composition of functions; • back-propagation and its relationship to the chain rule of differential calculus. We describe a “deep” neural network of “width” one. Deep means that the network composes a large number of functions organized into nodes of a graph. Width refers to the number of right hand side variables on the right hand side of the function being approximated. Setting “width” to one means that the network composes just univariate functions. Linear regression is a standard tool for analyzing the relationship between two or more variables. In this lecture, we’ll use the Python package statsmodels to estimate, interpret, and visualize linear regression models.