BOOKS - Machine Learning and Granular Computing A Synergistic Design Environment
Machine Learning and Granular Computing A Synergistic Design Environment - Witold Pedrycz, Shyi-Ming Chen 2024 PDF | EPUB Springer BOOKS
1 TON

Views
77645

Telegram
 
Machine Learning and Granular Computing A Synergistic Design Environment
Author: Witold Pedrycz, Shyi-Ming Chen
Year: 2024
Format: PDF | EPUB
File size: 74.0 MB
Language: ENG



Pay with Telegram STARS
The book "Machine Learning and Granular Computing A Synergistic Design Environment" is a groundbreaking work that explores the intersection of machine learning and granular computing, two rapidly evolving fields that are transforming the way we approach problem-solving and decision-making in various industries. The authors, experts in their respective fields, provide a comprehensive overview of these technologies and demonstrate how they can be combined to create a powerful synergistic design environment. The book begins by discussing the fundamentals of machine learning and granular computing, explaining the concepts and techniques that underlie these technologies. It then delves into the practical applications of these technologies in various domains such as healthcare, finance, and education, showcasing real-world examples of how they have been successfully implemented. One of the key themes of the book is the need to study and understand the process of technology evolution. The authors argue that this is essential for developing a personal paradigm for perceiving the technological process of developing modern knowledge, which is crucial for the survival of humanity and the unification of people in a warring state. They emphasize the importance of recognizing the interconnectedness of technologies and understanding how they build upon one another to create a more robust and effective system.
Книга «Machine arning and Granular Computing A Synergistic Design Environment» - это новаторская работа, в которой исследуется пересечение машинного обучения и гранулярных вычислений, двух быстро развивающихся областей, которые меняют подход к решению проблем и принятию решений в различных отраслях. Авторы, эксперты в своих областях, предоставляют всесторонний обзор этих технологий и демонстрируют, как их можно объединить для создания мощной синергетической среды проектирования. Книга начинается с обсуждения основ машинного обучения и гранулярных вычислений, объяснения концепций и методов, лежащих в основе этих технологий. Затем он углубляется в практическое применение этих технологий в различных областях, таких как здравоохранение, финансы и образование, демонстрируя реальные примеры того, как они были успешно реализованы. Одна из ключевых тем книги - необходимость изучения и понимания процесса эволюции технологий. Авторы утверждают, что это существенно для выработки личностной парадигмы восприятия технологического процесса развития современного знания, имеющего решающее значение для выживания человечества и объединения людей в воюющем государстве. Они подчеркивают важность признания взаимосвязанности технологий и понимания того, как они опираются друг на друга для создания более надежной и эффективной системы.
''

You may also be interested in:

Machine Learning Hero Master Data Science with Python Essentials Machine Learning with Python Hands-On Guide from Beginner to Expert (Mastering the AI Revolution Book 1)
Fundamentals of Machine & Deep Learning A Complete Guide on Python Coding for Machine and Deep Learning with Practical Exercises for Learners (Sachan Book 102)
Hacker|s Guide to Machine Learning with Python Hands-on guide to solving real-world Machine Learning problems with Scikit-Learn, TensorFlow 2, and Keras
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning
Python Machine Learning Is The Complete Guide To Everything You Need To Know About Python Machine Learning Keras, Numpy, Scikit Learn, Tensorflow, With Useful Exercises and examples
Python Machine Learning A Hands-On Beginner|s Guide to Effectively Understand Artificial Neural Networks and Machine Learning Using Python
Ultimate Machine Learning with ML.NET Build, Optimize, and Deploy Powerful Machine Learning Models for Data-Driven Insights with ML.NET, Azure Functions, and Web API
Python Machine Learning Understand Python Libraries (Keras, NumPy, Scikit-lear, TensorFlow) for Implementing Machine Learning Models in Order to Build Intelligent Systems
Ultimate Parallel and Distributed Computing with Julia For Data Science: Excel in Data Analysis, Statistical Modeling and Machine Learning by … to optimize workflows (English Edition)
Data Science and Machine Learning Interview Questions Using R: Crack the Data Scientist and Machine Learning Engineers Interviews with Ease
Data Science and Machine Learning Interview Questions Using R Crack the Data Scientist and Machine Learning Engineers Interviews with Ease
Financial Modeling Using Quantum Computing: Design and manage quantum machine learning solutions for financial analysis and decision making
Ultimate Machine Learning with ML.NET: Build, Optimize, and Deploy Powerful Machine Learning Models for Data-Driven Insights with ML.NET, Azure Functions, and Web API (English Edition)
Python Machine Learning for Beginners Unlocking the Power of Data. A Beginner|s Guide to Machine Learning with Python
Python Machine Learning for Beginners: Unlocking the Power of Data. A Beginner|s Guide to Machine Learning with Python
Python Machine Learning for Beginners Unlocking the Power of Data. A Beginner|s Guide to Machine Learning with Python
Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
The Art of Machine Learning: A Hands-On Guide to Machine Learning with R
The Art of Machine Learning A Hands-On Guide to Machine Learning with R
Machine Learning Q and AI 30 Essential Questions and Answers on Machine Learning and AI
The Art of Machine Learning A Hands-On Guide to Machine Learning with R
Machine Learning Q and AI 30 Essential Questions and Answers on Machine Learning and AI
Practical Automated Machine Learning on Azure Using Azure Machine Learning to Quickly Build AI Solutions, First Edition
Python Machine Learning: Leveraging Python for Implementing Machine Learning Algorithms and Applications (2023 Guide)
Machine Learning with Python Comprehensive Beginner’s Guide to Machine Learning in Python with Exercises and Case Studies
Machine Learning with Rust: A practical attempt to explore Rust and its libraries across popular machine learning techniques
Machine Learning with Rust A practical attempt to explore Rust and its libraries across popular Machine Learning techniques
Machine Learning With Python A Comprehensive Beginners Guide to Learn the Realms of Machine Learning with Python
Machine Learning for Finance Beginner|s guide to explore machine learning in banking and finance
Image Processing and Machine Learning, Volume 2 Advanced Topics in Image Analysis and Machine Learning
The Definitive Guide to Machine Learning Operations in AWS Machine Learning Scalability and Optimization with AWS
Machine Learning A Comprehensive, Step-by-Step Guide to Intermediate Concepts and Techniques in Machine Learning
Google JAX Essentials A quick practical learning of blazing-fast library for Machine Learning and Deep Learning projects
Shallow Learning vs. Deep Learning A Practical Guide for Machine Learning Solutions
Shallow Learning vs. Deep Learning A Practical Guide for Machine Learning Solutions
Ultimate Java for Data Analytics and Machine Learning: Unlock Java|s Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (English Edition)
Ultimate Machine Learning with Scikit-Learn Unleash the Power of Scikit-Learn and Python to Build Cutting-Edge Predictive Modeling Applications and Unlock Deeper Insights Into Machine Learning
Ultimate Machine Learning with Scikit-Learn Unleash the Power of Scikit-Learn and Python to Build Cutting-Edge Predictive Modeling Applications and Unlock Deeper Insights Into Machine Learning
Machine Learning For Beginners Step-by-Step Guide to Machine Learning, a Beginners Approach to Artificial Intelligence, Big Data, Basic Python Algorithms, and Techniques for Business (Practical Exampl
Ultimate Machine Learning with Scikit-Learn Unleash the Power of Scikit-Learn and Python to Build Cutting-Edge Predictive Modeling Applications and Unlock Deeper Insights Into Machine Learning