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.
The Bedouin in the Negev region have undergone a remarkable change of life style in the course of the 20th century: within a few generations they changed from being nomads to an almost sedentary and highly educated population. The author, who is a Bedouin himself and has worked in the Israeli Ministry of Education and Culture as Superintendent of the Bedouin Educational Schools in the Negev for many years, offers the first in-depth study of the development of Bedouin society, using the educational system as his focus.
Modern medicine has penetrated Bedouin tribes in the course of rapid urbanization and education, but when serious illnesses strike, particularly in the case of incurable diseases, even educated people turn to traditional medicine for a remedy. Over the course of 30 years, the author gathered data on traditional Bedouin medicine among pastoral-nomadic, semi-nomadic, and settled tribes. Based on interviews with healers, clients, and other active participants in treatments, this book will contribute to renewed thinking about a synthesis between traditional and modern medicine — to their reciprocal enrichment.
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