Book Details
Format
Kindle
Pages
670
Language
English
Published
Nov 23, 2021
Publisher
Springer
ISBN-10
3030916081
ISBN-13
9783030916084
Description
At the heart of the 22nd International Conference on Intelligent Data Engineering and Automated Learning lies a collection of innovative research and discussions presented by experts in the field. This compilation showcases cutting-edge insights into data engineering, automation, and machine learning, reflecting the latest advancements and trends. The contributions from esteemed authors paint a vibrant picture of how intelligent systems can enhance decision-making and operational efficiency in various domains.
The proceedings include rigorous peer-reviewed papers that delve into theoretical frameworks, practical applications, and emerging technologies. Readers will find topics ranging from data manipulation and processing to advanced learning algorithms, all designed to inspire further research and development. This book serves as a valuable resource for scholars, industry professionals, and anyone interested in the intersection of data science and artificial intelligence.
With a warm invitation to explore new ideas and methodologies, it encourages collaboration and dialogue within the scientific community. Ultimately, this work not only highlights significant achievements in intelligent data engineering but also paves the way for future innovations that will shape the landscape of automated learning.
The proceedings include rigorous peer-reviewed papers that delve into theoretical frameworks, practical applications, and emerging technologies. Readers will find topics ranging from data manipulation and processing to advanced learning algorithms, all designed to inspire further research and development. This book serves as a valuable resource for scholars, industry professionals, and anyone interested in the intersection of data science and artificial intelligence.
With a warm invitation to explore new ideas and methodologies, it encourages collaboration and dialogue within the scientific community. Ultimately, this work not only highlights significant achievements in intelligent data engineering but also paves the way for future innovations that will shape the landscape of automated learning.
Genres
Science & Technology