Feature and Dimensionality Reduction for Clustering with Deep Learning is popular PDF and ePub book, written by Frederic Ros in 2024-01-22, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Feature and Dimensionality Reduction for Clustering with Deep Learning can be Read Online from any device for your convenience.

Feature and Dimensionality Reduction for Clustering with Deep Learning Book PDF Summary

This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by “family” to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.

Detail Book of Feature and Dimensionality Reduction for Clustering with Deep Learning PDF

Feature and Dimensionality Reduction for Clustering with Deep Learning
  • Author : Frederic Ros
  • Release : 22 January 2024
  • Publisher : Springer Nature
  • ISBN : 9783031487439
  • Genre : Technology & Engineering
  • Total Page : 273 pages
  • Language : English
  • PDF File Size : 18,5 Mb

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