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.

Название: Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide
Автор: Van Thanh Tien Nguyen, Nhut T.M. Vo, Van Chinh Truong
Издательство: CRC Press
Год: 2025
Страниц: 361
Язык: английский
Формат: pdf (true)
Размер: 13.4 MB

As multicriteria decision-making (MCDM) continues to grow and evolve, Machine Learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples, it showcases the effectiveness of these techniques in optimal design. The book also provides a comparative analysis of conventional MCDM algorithms and Machine Learning techniques, enabling readers to make informed decisions about their use in different scenarios. This book is designed for professionals, researchers, and practitioners in engineering, Computer Science, sustainability, and related fields. It is also a valuable resource for students and academics who wish to expand their knowledge of Machine Learning applications in multicriteria decision-making.

Название: Artificial Intelligence: Technical and Societal Advancements
Автор: Utku Kose, Mustafa Umut Demirezen
Издательство: CRC Press
Год: 2025
Страниц: 349
Язык: английский
Формат: pdf (true)
Размер: 36.8 MB

This book provides an examination of cutting-edge research and developments in the field of Artificial Intelligence (AI). It seeks to extend the view in both technical and societal evaluations to ensure a well-defined balance for societal outcomes. It explores hot topics such as Generative Artificial Intelligence (GenAI), Artificial Intelligence in law, education, and climate change. Artificial Intelligence: Technical and Societal Advancements seeks to bridge the gap between theory and practical applications of AI by giving readers insight into recent advancements. It offers readers a deep dive into the transformative power of AI for the present and future world. As Artificial Intelligence continues to revolutionize various sectors, the book discusses applications from healthcare to finance and from entertainment to industrial areas. It discusses the technical aspects of intelligent systems and the effects of these aspects on humans. To this point, this book considers technical advancements while discussing the societal pros and cons in terms of human-machine interaction in critical applications. The target readers of this book include academicians; researchers; experts; policymakers; educators; and B.S., M.S., and Ph.D. students in the context of target problem fields. It can be used accordingly as a reference source and even supportive material for Artificial Intelligence-oriented courses.

Название: Supply Chain Software Security: AI, IoT, and Application Security
Автор: Aamiruddin Syed
Издательство: Apress
Год: 2024
Страниц: 533
Язык: английский
Формат: pdf
Размер: 10.1 MB

Delve deep into the forefront of technological advancements shaping the future of supply chain safety and resilience. In an era where software supply chains are the backbone of global technology ecosystems, securing them against evolving threats has become mission critical. This book offers a comprehensive guide to understanding and implementing next-generation strategies that protect these intricate networks from most pressing risks. This book begins by laying the foundation of modern software supply chain security, exploring the shifting threat landscape and key technologies driving the future. Through real-world case studies and practical insights, learn how to build resilient supply chains equipped to defend against sophisticated attacks like dependency confusion, backdoor injection, and adversarial manipulation. Whether you're managing a global software operation or integrating DevSecOps into your CI/CD pipelines, this book offers actionable advice for fortifying your supply chain end-to-end. The target audience for a book would typically include professionals and individuals with an interest or involvement in cloud-native application development and DevOps practices.