Название: Learning Automata and Their Applications to Intelligent Systems
Автор: JunQi Zhang, MengChu Zhou
Издательство: Wiley-IEEE Press
Год: 2024
Страниц: 275
Язык: английский
Формат: pdf (true), epub
Размер: 21.6 MB

Comprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed. Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata. As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application. The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, ranking, and scheduling. A timely text in a rapidly developing field,Learning Automata and Their Applications to Intelligent Systems is an essential resource for researchers in Machine Learning, engineering, operation, and management. The book is also highly suitable for graduate level courses on Machine Learning, soft computing, reinforcement learning and stochastic optimization.

Название: Дискретная математика для программистов
Автор: Новиков Ф.А.
Издательство: СПб: Питер
Год: 2000
Cтраниц: 304
Формат: pdf
Размер: 11 мб
Язык: русский

В учебнике изложены основные разделы дискретной математики и описаны важнейшие алгоритмы на дискретных структурах данных. Основу книги составляет материал лекционного курса, который автор читает в Санкт-Петербургском государственном техничесском университете последние полтора десятилетия. Для студентов вузов, практикующих программистов и всех желающих изучить дискретную математику.

Название: C# 12 Pocket Reference: Instant Help for C# 12 Programmers
Автор: Joseph Albahari, Ben Albahari
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 287
Язык: английский
Формат: True PDF, True EPUB (Retail Copy), AZW3 (conv), MOBI (conv)
Размер: 10.1 MB

Looking for quick answers for using C# 12? This tightly focused and practical guide tells you exactly what you need to know without long intros or bloated samples. Succinct and easy to browse, this pocket reference is an ideal quick source of information. If you know Java, C++, or an earlier C# version, this guide will help you get rapidly up to speed. All programs and code snippets are available as interactive samples in LINQPad. You can edit these samples and instantly see the results without needing to set up projects in Visual Studio.

Название: Linux Coding & Programming Tricks & Tips - 16th Edition, 2023
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2023
Язык: английский
Формат: pdf
Размер: 38.4 MB

"Трюки и советы по кодированию и программированию в Linux" - это идеальное цифровое издание для тех, кто стремится поднять свои навыки на новый уровень. Вы хотите улучшить работу пользователей? Или вы хотите получить глубокие знания? Хотите учиться непосредственно у экспертов в данной области? Хотите изучить множество приемов, используемых профессионалами? В новом руководстве "Трюки и советы по кодированию и программированию в Linux" вы узнаете все, что необходимо знать, чтобы стать более уверенным, квалифицированным и опытным пользователем. Пользователем, который получает максимальную отдачу от программирования на Python и C++ и самой Linux. Мы научим Вас навыкам, которые разрабатывались специально для Вас на протяжении десятилетий.

Название: 12 Twisted Python Projects for Young Coders (MEAP v6)
Автор: Daniel Aldred
Издательство: Manning Publications
Год: 2023
Страниц: 230
Язык: английский
Формат: pdf
Размер: 22.2 MB

You won’t find these Python projects in a programming textbook! Each twisted task teaches you Python GUI skills you’ll use again and again—even for serious things like a job! 12 Twisted Python Projects for Young Coders helps you take your next steps in Python by creating offbeat projects you’ll love to code. You’ll learn vital techniques for designing and developing Graphic User Interfaces (GUIs) that put a face on your Python apps. Use the open-source GUIZero library to build programs that prank your friends and amuse your family while upgrading your programming skills. Perfect for Python beginners, and kids big and small. The button, boxes, menus, and images on a Graphical User Interface (GUI) makes it easy for users to interact with a program. Python’s free, open source GUIZero library makes it easy to create GUIs for your applications. Built on the rock-solid Python Tkinter GUI, GUIZero is perfect for creating simple forms, games, and widgets. Are you a Python beginner wondering where to go next? 12 Twisted Python Projects for Young Coders has some wicked answers! You’ll build the kind of projects you’d never find in computer class, and learn important Python development skills as you do. For Python beginners who know the absolute basics, and experienced Python programmers looking for fun projects to try.

Название: Methods and Applications of Autonomous Experimentation
Автор: Marcus M. Noack, Daniela Ushizima
Издательство: CRC Press
Серия: Chapman & Hall/CRC Computational Science
Год: 2024
Страниц: 445
Язык: английский
Формат: pdf (true)
Размер: 41.3 MB

Autonomous Experimentation is poised to revolutionize scientific experiments at advanced experimental facilities. Whereas previously, human experimenters were burdened with the laborious task of overseeing each measurement, recent advances in mathematics, machine learning and algorithms have alleviated this burden by enabling automated and intelligent decision-making, minimizing the need for human interference. Illustrating theoretical foundations and incorporating practitioners’ first-hand experiences, this book is a practical guide to successful Autonomous Experimentation. Just like so many other topics that have been adopted into the realm of Machine Learning and AI—Deep Learning, digital twins, active learning, and so on—Autonomous Experimentation has become a fuzzy, ill-defined ideal everyone wants, but seemingly no one can deliver. The main reason for that is the missing, inherent meaning of the term “Autonomous Experimentation”. In this book, we want to separate the practical methods and applications from the buzz and hype surrounding the term. Autonomous Experimentation (AE) is an emerging paradigm for accelerating scientific discovery, leveraging Artificial Intelligence and Machine Learning methods to automate the entire experimental loop, including the decision-making step. AE combines advancements in hardware automation, data analytics, modeling, and active learning to augment a scientific instrument, enabling it to autonomously explore the search space corresponding to a problem of interest.

Название: Toward Artificial General Intelligence: Deep Learning, Neural Networks, Generative AI
Автор: Victor Hugo C. de Albuquerque, Pethuru Raj, Satya Prakash Yadav
Издательство: De Gruyter
Год: 2024
Страниц: 424
Язык: английский
Формат: pdf (true), epub, mobi
Размер: 10.1 MB

Artificial Intelligence (AI) has been an exciting field of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL) algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision (CV) and natural language processing (NLP), the primary use cases and applications of AI. The book has well-written chapters for demystifying AI model engineering methods. Further on, our esteemed readers can find details on AI model evaluation, optimization, deployment and observability. Finally, the book deals and describes generative AI, the latest buzzword in the IT industry.

Название: Coding Art: A Guide to Unlocking Your Creativity with the Processing Language and p5.js in Four Simple Steps, Second Edition
Автор: Mathias Funk, Yu Zhang
Издательство: Apress
Год: 2024
Страниц: 342
Язык: английский
Формат: pdf, epub
Размер: 11.9 MB

Finally, a book on creative programming, written directly for artists and designers! This second edition offers expanded and updated content incorporating the latest advancements and trends in the field of creative programming, also for creatives who want to work directly with P5.js and online. It delves deeper into the intricacies of computational art. It includes fresh case studies that explore real-world applications of coding art, inspiring readers to think beyond traditional boundaries. Rather than following a computer science curriculum, this book is aimed at creatives who are working in the intersection of design, art, and education. Following a real-world use case of computation art, you'll see how it relates back to the four key pillars, and addresses potential pitfalls and challenges in the creative process. All code examples are presented in a fully integrated Processing example library, making it easy for readers to get started. This unique and finely balanced approach between skill acquisition and development makes Coding Art, Second Edition the ideal reference book for both creative programming and the creative process for professors and students alike. Processing and p5.js are not only versatile frameworks internally (with all included functionality). With these platforms, you can reach into a vast ecosystem of functions implemented in languages like Java, Groovy, Scala, Kotlin, and Clojure (for Processing) and jаvascript for p5.js.

Название: Google Cloud Platform for Data Science: A Crash Course on Big Data, Machine Learning, and Data Analytics Services
Автор: Shitalkumar R. Sukhdeve, Sandika S. Sukhdeve
Издательство: Apress
Год: 2024
Страниц: 231
Язык: английский
Формат: pdf
Размер: 10.2 MB

This book is your practical and comprehensive guide to learning Google Cloud Platform (GCP) for Data Science, using only the free tier services offered by the platform. Data Science and Machine Learning are increasingly becoming critical to businesses of all sizes, and the cloud provides a powerful platform for these applications. GCP offers a range of Data Science services that can be used to store, process, and analyze large datasets, and train and deploy Machine Learning models. The book is organized into seven chapters covering various topics such as GCP account setup, Google Colaboratory, Big Data and Machine Learning, Data Visualization and Business Intelligence, Data Processing and Transformation, Data Analytics and Storage, and Advanced Topics. Each chapter provides step-by-step instructions and examples illustrating how to use GCP services for Data Science and Big Data projects. Readers will learn how to set up a Google Colaboratory account and run Jupyter notebooks, access GCP services and data from Colaboratory, use BigQuery for data analytics, and deploy Machine Learning models using Vertex AI. For Data scientists, machine learning engineers, and analysts who want to learn how to use Google Cloud Platform (GCP) for their Data Science and Big Data projects.

Название: Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python 2nd Edition
Автор: Shamshad Ansari
Издательство: Apress
Год: 2023
Страниц: 541
Язык: английский
Формат: pdf
Размер: 18.6 MB

Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition’s publication. All code used in the book has also been fully updated. This second edition features new material covering image manipulation practices, image segmentation, feature extraction, and object identification using real-life scenarios to help reinforce each concept. These topics are essential for building advanced computer vision applications, and you’ll gain a thorough understanding of them. The book’s source code has been updated from TensorFlow 1.x to 2.x, and includes step-by-step examples using both OpenCV and TensorFlow with Python. Those who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.