Название: Mastering ARKit: Apple's Augmented Reality App Development Platform, 2nd Edition
Автор: Jayven Nhan
Издательство: Apress
Год: 2024
Страниц: 347
Язык: английский
Формат: pdf
Размер: 10.7 MB

Embark on a journey to build an augmented reality world. This book puts theory into practical application by building unique augmented reality apps specific to each chapter’s topic. You’ll learn to engineer successful, well-designed, and comprehensive augmented reality applications for iOS devices. This updated edition has been thoroughly revised to cover the latest advancements in iOS 17 and Xcode 15, equipping you with the knowledge and tools to build cutting-edge augmented reality experiences. Starting with the foundation of augmented reality on Apple platforms, you will understand the building blocks and inner workings of the technologies that power augmented reality. Then, delve into the practicalities of building AR apps using ARKit, SceneKit, SpriteKit, RealityKit, and integrating with SwiftUI and advanced features like ReplayKit for recording experiences. For iOS developers who want to expand their knowledge of ARKit. Ideal for those with a solid foundation in Swift and familiarity with Xcode, seeking to explore the expansive capabilities of augmented reality on Apple devices.

Название: Effective Python: 125 Specific Ways to Write Better Python, 3rd Edition (Final Release)
Автор: Brett Slatkin
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2025
Страниц: 672
Язык: английский
Формат: epub (true)
Размер: 82.2 MB

Master the art of Python programming with 125 actionable best practices to write more efficient, readable, and maintainable code. Python is a versatile and powerful language, but leveraging its full potential requires more than just knowing the syntax. Effective Python: 125 Specific Ways to Write Better Python, 3rd Edition is your comprehensive guide to mastering Python's unique strengths and avoiding its hidden pitfalls. This updated edition builds on the acclaimed second edition, expanding from 90 to 125 best practices that are essential for writing high-quality Python code. Drawing on years of experience at Google, Brett Slatkin offers clear, concise, and practical advice for both new and experienced Python developers. Each item in the book provides insight into the "Pythonic" way of programming, helping you understand how to write code that is not only effective but also elegant and maintainable. Whether you're building web applications, analyzing data, writing automation scripts, or training AI models, this book will equip you with the skills to make a significant impact using Python.

Название: Введение в Rust
Автор: Максим Смирнов
Издательство: Stepik
Год: 2024
Формат: HTML
Страниц: много
Размер: 212 Mb
Язык: Русский

Этот курс идеально подойдет для тех кто имеет начальные навыки программирования или их вовсе нет. Весь материал преподнесен очень понятным языком и без воды. В самом курсе вы освоите базу программирования, а именно: переменные, основные структуры данных, арифметические операции, методы, функции, поймете рекурсию и многое чего другого.

Название: MATLAB Deep Learning Toolbox User’s Guide (R2024b)
Автор: Mark Hudson Beale, Martin T. Hagan, Howard B. Demuth
Издательство: The MathWorks, Inc.
Год: September 2024
Страниц: 5466
Язык: английский
Формат: pdf (true)
Размер: 86.1 MB

Deep Learning (DL) is a branch of Machine Learning (ML) that teaches computers to do what comes naturally to humans: learn from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. Deep Learning is especially suited for image recognition, which is important for solving problems such as facial recognition, motion detection, and many advanced driver assistance technologies such as autonomous driving, lane detection, pedestrian detection, and autonomous parking. Deep Learning Toolbox provides simple MATLAB commands for creating and interconnecting the layers of a deep neural network. Examples and pretrained networks make it easy to use MATLAB for deep learning, even without knowledge of advanced computer vision algorithms or neural networks. Deep Learning Toolbox provides a framework for designing and implementing deep neural networks with algorithms, pretrained models, and apps. You can exchange models with TensorFlow and PyTorch through the ONNX format and import models from TensorFlow-Keras and Caffe. The toolbox supports transfer learning with DarkNet-53, ResNet-50, NASNet, SqueezeNet and many other pretrained models.

Название: Mastering Algorithm in Python
Автор: Ed Norex
Издательство: HiTeX Press
Год: 2024
Страниц: 556
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Master the art of solving complex problems with "Mastering Algorithm in Python," your comprehensive guide to understanding and applying algorithms using one of the most versatile programming languages. Whether you're a beginner eager to dive into the world of Computer Science or a seasoned professional looking to sharpen your skills, this book covers everything from fundamental concepts to advanced techniques. Unlock the secrets of data structures, delve into the intricacies of searching and sorting algorithms, navigate through the complexities of graph algorithms, and conquer challenges with dynamic programming, greedy algorithms, divide and conquer strategies, and backtracking algorithms. Elevate your expertise further as you explore advanced topics including Machine Learning and graphical models, all illustrated through clear, practical Python examples.

Название: Explainable Machine Learning for Geospatial Data Analysis: A Data-Centric Approach
Автор: Courage Kamusoko
Издательство: CRC Press
Год: 2025
Страниц: 280
Язык: английский
Формат: pdf (true), epub
Размер: 44.9 MB

Explainable Machine Learning (XML), a subfield of Artificial Intelligence (AI), is focused on making complex AI models understandable to humans. This book highlights and explains the details of Machine Learning models used in geospatial data analysis. It demonstrates the need for a data-centric, explainable Machine Learning approach to obtain new insights from geospatial data. It presents the opportunities, challenges, and gaps in the Machine Learning and Deep Learning approaches for geospatial data analysis and how they are applied to solve various environmental problems in land cover changes and in modeling forest canopy height and aboveground biomass density. The author also includes guidelines and code scripts (R, Python) valuable for practical readers.

Название: Паттерны проектирования jаvascript: Создаем быстрые и эффективные приложения любого масштаба
Автор: Уго Ди Франческо
Издательство: Спринт Бук
Год: 2025
Страниц: 304
Язык: русский
Формат: pdf
Размер: 21.8 MB

Раскройте потенциал паттернов проектирования jаvascript. Найдите структурированные решения распространенных задач разработки, пригодные для многократного использования и повышающие масштабируемость, производительность и удобство сопровождения кода. Узнайте, как применение этих паттернов позволяет создавать более чистый и понятный код, способствует организации совместной работы в команде, сокращает количество ошибок и экономит время и силы. Автор дает исчерпывающее представление о паттернах проектирования в современном jаvascript (ES6+) и приводит практические примеры их применения. Сначала вы познакомитесь с порождающими, структурными и поведенческими паттернами проектирования в идиоматическом для jаvascript стиле, а затем переключитесь на архитектурные паттерны и паттерны пользовательского интерфейса. Вы узнаете, как применять паттерны, характерные для таких библиотек, как React, и распространять их на фронтенд и микрофронтенд.

Название: Explainable Artificial Intelligence: A Practical Guide
Автор: Parikshit Narendra Mahalle, Yashwant Sudhakar Ingle
Издательство: River Publishers
Год: 2024
Страниц: 104
Язык: английский
Формат: pdf (true), epub
Размер: 14.6 MB

This book explores the growing focus on Artificial Intelligence (AI) systems in both industry and academia. Explainable Artificial Intelligence (XAI) comprises a set of frameworks and tools to assist us in forecasting futuristic events with the aid of Machine Learning/evolutionary and intelligent techniques. XAI helps to improve the performance of the automated models and to train the automated tools for diverse engineering purposes. XAI can also assist in the generation of feature attributions for forecasting the model behavior with respect to different inputs. XAI is used in diverse fields such as marketing, Data Science, engineering, medical science, and economics. Explainable Artificial Intelligence: A Practical Guide is a comprehensive guide to the reader which covers the fundamentals of traditional AI to the current status of XAI. In a nutshell, this book puts forward the best research roadmaps, strategies and challenges to design and develop XAI applications.

Название: MATLAB Statistics and Machine Learning Toolbox User’s Guide (R2024b)
Автор: The MathWorks
Издательство: The MathWorks, Inc.
Год: September 2024
Страниц: 12578
Язык: английский
Формат: pdf (true)
Размер: 57.4 MB

"Инструментарий статистики и машинного обучения" предоставляет функции и приложения для описания, анализа и моделирования данных. Вы можете использовать описательную статистику, визуализацию и кластеризацию для анализа данных, сопоставления распределений вероятностей с данными, генерации случайных чисел для моделирования методом Монте-Карло и проверки гипотез. Алгоритмы регрессии и классификации позволяют вам делать выводы на основе данных и использовать приложение Classification и Regression Learner или использовать AutoML для интерактивного анализа. Для анализа многомерных данных и извлечения признаков инструментарий предоставляет методы анализа основных компонентов (PCA), регуляризации, сокращения и выбора признаков, которые помогут вам получить наилучшие прогнозы.

Название: High-Performance Algorithmic Trading Using AI: Strategies and Insights for Developing Cutting-Edge Trading Algorithms
Автор: Melick R. Baranasooriya
Издательство: BPB Publications
Год: 2024
Страниц: 358
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

"High-Performance Algorithmic Trading using AI" is a comprehensive guide designed to empower both beginners and experienced professionals in the finance industry. This book equips you with the knowledge and tools to build sophisticated, high-performance trading systems. It starts with basics like data preprocessing, feature engineering, and ML. Then, it moves to advanced topics, such as strategy development, backtesting, platform integration using Python for financial modeling, and the implementation of AI models on trading platforms. Each chapter is crafted to equip readers with actionable skills, ranging from extracting insights from vast datasets to developing and optimizing trading algorithms using Python's extensive libraries. It includes real-world case studies and advanced techniques like Deep Learning and reinforcement learning. The book wraps up with future trends, challenges, and opportunities in algorithmic trading.