Recent Trends And Future Challenges In Learning From Data
Download Recent Trends And Future Challenges In Learning From Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Recent Trends And Future Challenges In Learning From Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Recent Trends and Future Direction for Data Analytics
In an increasingly data-centric world, scholars and practitioners grapple with the complexities of harnessing data analytics effectively across various industries. The challenge lies in navigating the rapid evolution of methodologies, identifying emerging trends, and understanding the nuanced applications of data analytics in real-world scenarios. This gap between theory and practice inhibits academic progress. It hampers industry innovation, leaving stakeholders needing help to leverage data to its full potential. Recent Trends and Future Direction for Data Analytics presents a compelling solution. By delving into real-world case studies spanning supply chain management, marketing, healthcare, and finance, this book bridges the gap between theory and practice, offering invaluable insights into the practical applications of data analytics. A systematic exploration of fundamental concepts, advanced techniques, and specialized topics equips scholars, researchers, and industry professionals with the knowledge and tools needed to navigate the complexities of data analytics with confidence.
Recent Trends and Future Challenges in Learning from Data
This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022. Highlighting the role of statistics in discovering novel and interesting patterns in the era of big data, it follows the motto of the conference: “Avoiding drowning in the data: recent trends and future challenges in learning from data”. The central focus is on multidisciplinary approaches to data analysis, classification, and the interface between computer science, data mining and statistics. Both methodological and applied topics are covered. The former includes supervised and unsupervised techniques with particular emphasis on advances in regression and clustering analysis and constructing composite indicators. The applications are mainly in risk analysis, biology, and education. The volume is organized into four main macro themes: methodological contributions in the social sciences and education, multivariate analysis methods for big data, innovative contributions for applications inspired by biology, and strategies for analyzing complex data in finance.
Proceedings of 5th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications
Author: Vinit Kumar Gunjan
language: en
Publisher: Springer Nature
Release Date: 2025-02-25
This book contains original, peer-reviewed research articles from the 5th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, held in Hyderabad, India on 28–29 March 2024. It includes the most recent research trends and advancements in machine learning, smart cities, IoT, AI, cyber-physical systems, cybernetics, data science, neural networks, and cognition. This book addresses the comprehensive nature of AI, ML, and DL to highlight its role in the modelling, identification, optimisation, prediction, forecasting, and control of future intelligent systems.