Название: Machine Learning and Granular Computing: A Synergistic Design Environment
Автор: Witold Pedrycz, Shyi-Ming Chen
Издательство: Springer
Год: 2024
Страниц: 355
Язык: английский
Формат: pdf (true), epub
Размер: 74.0 MB

This volume provides the reader with a comprehensive and up-to-date treatise positioned at the junction of the areas of Machine Learning (ML) and Granular Computing (GrC). ML offers a wealth of architectures and learning methods. Granular Computing addresses useful aspects of abstraction and knowledge representation that are of importance in the advanced design of ML architectures. In unison, ML and GrC support advances of the fundamental learning paradigm. As built upon synergy, this unified environment focuses on a spectrum of methodological and algorithmic issues, discusses implementations and elaborates on applications. The chapters bring forward recent developments showing ways of designing synergistic and coherently structured ML-GrC environment. Machine Learning has been an intensive research endeavor leading in recent years to a wealth of concepts, algorithms, and implementations encompassing a variety of original and far-reaching application domains. The successes of designed learning environments are highly impactful, especially in the realm of natural language processing (NLP) as well as image processing and computer vision. The book will be of interest to a broad audience including researchers and practitioners active in the area of ML or GrC and interested in following its timely trends and new pursuits.

Название: Artificial Intelligence in Prescriptive Analytics: Innovations in Decision Analysis, Intelligent Optimization, and Data-Driven Decisions
Автор: Witold Pedrycz, Gilberto Rivera, Eduardo Fernández, Gustavo Javier Meschino
Издательство: Springer
Год: 2024
Страниц: 544
Язык: английский
Формат: pdf (true)
Размер: 32.5 MB

Considering the advances of the different approaches and applications in the last years, and even in the last months, this is a particular moment in history to transform every data-driven decision-making process with the power of Artificial Intelligence (AI). This book reveals, through concrete case studies and original application ideas, how cutting-edge AI techniques are revolutionizing industries such as finance, health care, and manufacturing. It invites us to discover how machine learning, decision analysis, and intelligent optimization are changing, directly or indirectly, almost all aspects of our daily lives. This comprehensive book offers practical insights and real-world applications for professionals, researchers, and students alike. It helps to learn how to apply AI for smarter, data-driven decisions in areas like supply chain management, risk assessment, and even personalized medicine. Be inspired by the chapters of this book and unlock the full potential of AI in your field!

Название: Analysis of Categorical Data with R, 2nd Edition
Автор: Christopher R. Bilder, Thomas M. Loughin
Издательство: CRC Press
Год: 2025
Страниц: 688
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The second edition is a substantial update of the first based on the authors’ experiences of teaching from the book for nearly a decade. The book is organized as before, but with new content throughout, and there are two new substantive topics in the advanced topics chapter—group testing and splines. The computing has been completely updated, with the "emmeans" package now integrated into the book. The book does not require any prior experience with R. We provide an introduction to the essential features and functions of R in Appendix A. We also provide introductory details on the use of R in the earlier chapters to help inexperienced R users. Throughout the book, as new R functions are needed, their basic features are discussed in the text and their implementation shown with corresponding output. We focus on using R packages that are provided by default with the initial R installation. However, we make frequent use of other R packages when they are significantly better or contain functionality unavailable in the standard R packages. The book contains the code and output as it would appear in the R Console; we make minor modifications at times to the output only to save space within the book. Code provided in the book for plotting is often meant for color display rather than the actual black-and-white display shown in the print and some electronic editions.

Название: Introduction to Python Network Automation Volume II: Stepping up: Beyond the Essentials for Success, 2nd Edition
Автор: Brendan Choi
Издательство: Apress
Год: 2024
Страниц: 797
Язык: английский
Формат: pdf (true), epub (true)
Размер: 41.1 MB

Continue your Python network automation journey and delve deeper into advanced techniques and methodologies. Volume 2 of this comprehensive guide takes you beyond the essentials, equipping you with advanced skills and strategies crucial for success in network automation. Building upon the knowledge gained in Volume 1, you’ll set the stage for mastery in this dynamic field. You’ll start by establishing a robust lab environment for advanced automation projects tailored to your needs and use practical exercises to gain valuable insights into essential networking protocols. Then automate repetitive tasks with precision and efficiency by leveraging powerful Python libraries and tools. You’ll also see how to streamline IP address management and data center infrastructure management tasks with Python. Discover advanced techniques for network management and monitoring to optimize network performance and security. Introduction to Python Network Automation Volume 2 - Stepping up provides a comprehensive roadmap to elevate your skills and excel in the dynamic field of network automation. Whether you're a seasoned professional or a newcomer to the field, this guide equips you with the tools and knowledge needed to thrive in today's network automation landscape. IT engineers and developers, network managers and students, who would like to learn network automation using Python.

Название: Mastering ChatGPT and Google Colab for Machine Learning: Automate AI Workflows and Fast-Track Your Machine Learning Tasks with the Power of ChatGPT, Google Colab, and Python
Автор: Rosario Moscato
Издательство: Orange Education Pvt Ltd, AVA
Год: 2024
Страниц: 386
Язык: английский
Формат: epub (true)
Размер: 135.7 MB

Learn how to harness the power of ChatGPT to streamline data analysis, accelerate model development, and unlock innovative solutions to real-world problems. Unlock the future of Machine Learning by mastering Google Colab, trusted by over 5 million data scientists, and ChatGPT, powering 100 million users worldwide. This book bridges the latest in AI with practical, hands-on applications for Data Science. With these game-changing tools at your command, you’ll be able to streamline complex workflows, automate tedious tasks, and propel your AI skills to new heights—making Machine Learning faster, smarter, and more accessible than ever before. Imagine having a personal assistant that not only helps you generate code but also completes it for you. Well, with ChatGPT, that’s exactly what you get. Let’s explore how you can harness the power of ChatGPT to create Python code tailored for analyzing datasets, preprocessing them, and building Machine Learning models, even with the free version. ChatGPT, in its free version, might surprise you with its ability to understand and generate Python code snippets. By providing it with context about your dataset and the task you want to perform, you can prompt it to generate code to help you with your analysis. This book is ideal for aspiring data scientists and Machine Learning enthusiasts eager to enhance their skills with ChatGPT and Google Colab. It also serves tech professionals, academics, and business analysts seeking practical insights into AI and Data Science. A basic understanding of programming, statistics, and data analysis is recommended before diving in.

Название: Coding jаvascript: Along with an introduction to HTML and CSS
Автор: Tom Henricksen
Издательство: Reedsy
Год: 2024
Страниц: 124
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

This book gives you a full review of jаvascript and introduces you to HTML and CSS. As a developer, I thought I knew enough of HTML and CSS. I was wrong. I had to come back to the basics again and again. That is why I put this together. Plus I feel like jаvascript should be here too. First, we start with some basics of HTML. You may have seen some of this before, but I find a review helpful. Then we cover some HTML5 changes. We touch on some of the major changes. Then we wrap up HTML with a discussion of tables, divs, and spans. These have confused me more than once... The second section is devoted to CSS. This helps class things up a bit. We cover CSS basics, the box model, and CSS3. Similar to HTML5 it has some interesting updates. The third part focuses on jаvascript basics. Covering topics like variables, functions, and conditionals. We also cover loops and closures too. In this quick start guide, we just focus on what you need to start working.

Название: Machine Learning for Real World Applications
Автор: Dinesh K. Sharma, H.S. Hota, Aaron Rasheed Rababaah
Издательство: Springer
Год: 2024
Страниц: 315
Язык: английский
Формат: pdf (true)
Размер: 24.9 MB

This book provides a comprehensive coverage of Machine Learning techniques ranging from fundamental to advanced. The content addresses topics within the scope of the book from the ground up, providing readers with a trustworthy source of theoretical and technical learning content. The book emphasizes not only the theoretical features but also their practical and implementation aspects in real-world applications. These applications are crucial because they provide comprehensive experimental work that supports the validity of the offered approaches as well as clear instructions on how to apply such models in comparable and distinct settings and contexts. Furthermore, the chapters shed light on the problems and possibilities that researchers might use to direct their future research efforts. The book is beneficial for undergraduate and postgraduate students, researchers, and industry personnel.

Название: Federated Learning for Smart Communication using IoT Application
Автор: Kaushal Kishor, Parma Nand, Vishal Jain, Neetesh Saxena, Gaurav Agarwal, Rani Astya
Издательство: CRC Press
Год: 2025
Страниц: 275
Язык: английский
Формат: pdf (true), epub
Размер: 12.8 MB

The effectiveness of Federated Learning (FL) in high‑performance information systems and informatics‑based solutions for addressing current information support requirements is demonstrated in this book. To address heterogeneity challenges in Internet of Things (IoT) contexts, Federated Learning for Smart Communication using IoT Application analyses the development of personalized Federated Learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT‑based human activity recognition to show the efficacy of personalized Federated Learning for intelligent IoT applications. Federated Learning (FL) is leading the way in revolutionary developments in Machine Learning, transforming the traditional field of centralized model training. Fundamentally, FL is a novel technique that enables a network of dispersed devices to jointly train Machine Learning models. FL prioritizes privacy above central processing of raw data, as is the case with traditional approaches. Individual devices—such as cellphones, edge devices, or other endpoints—contribute to model training under this novel paradigm without disclosing private information. We will explore the fundamentals of FL, its uses, and its potential to revolutionize the ever-evolving field of Artificial Intelligence (AI) as we delve into its depths. This book is recommended for anyone interested in Federated Learning‑based intelligent algorithms for smart communications.

Название: Command-Query Responsibility Segregation (CQRS): by Example
Автор: Carlos Buenosvinos, Christian Soronellas, Keyvan Akbary
Издательство: Leanpub
Год: 2024-09-02
Страниц: 236
Язык: английский
Формат: epub
Размер: 17.5 MB

This course balances theory with practical implementation. You'll learn through real-world examples, starting with the fundamentals and moving to advanced CQRS techniques. Each concept is accompanied by hands-on exercises to solidify your understanding.Learn the CQRS pattern through hands-on examples. Understand how to design scalable systems by separating commands and queries, and implement best practices for improved performance and flexibility. This course offers an in-depth exploration of the Command Query Responsibility Segregation (CQRS) pattern, a powerful architecture design that separates read and write operations to achieve greater scalability and performance in software systems. You'll begin by understanding the core principles behind CQRS and why it is essential for handling complex, high-traffic applications. Throughout the course, we’ll work through real-world examples that demonstrate how to apply CQRS to achieve a cleaner and more efficient codebase. By the end of the course, you will have a comprehensive understanding of CQRS and its benefits. This course is ideal for software developers, solution architects, and technical leads who are looking to enhance their knowledge of scalable system design. It is particularly suited for professionals working on high-traffic, data-intensive applications where performance and maintainability are critical. Additionally, developers familiar with domain-driven design, microservices, or event-driven architectures will find this course highly relevant. While prior knowledge of CQRS is not required, a foundational understanding of database design and system workflows will be beneficial.

Название: A Common-Sense Guide to Data Structures and Algorithms in jаvascript: Level Up Your Core Programming Skills, Volume 1
Автор: Jay Wengrow
Издательство: Pragmatic Bookshelf
Год: August 2024 (P1.0)
Страниц: 516
Язык: английский
Формат: True EPUB (Retail Copy)
Размер: 19.99 MB

If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your jаvascript code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The jаvascript edition uses jаvascript exclusively for all code examples, exercises, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your jаvascript code faster and more scalable.