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Data Mining
Data mining is a branch of computer science that is used to automatically extract meaningful, useful knowledge and previously unknown, hidden, interesting patterns from a large amount of data to support the decision-making process. This book presents recent theoretical and practical advances in the field of data mining. It discusses a number of data mining methods, including classification, clustering, and association rule mining. This book brings together many different successful data mining studies in various areas such as health, banking, education, software engineering, animal science, and the environment.
Data Mining
The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.
Dijital Dönüşüm ve Finans: Gelecek Sandığımızdan Daha Yakın
İnsanlık tarihi boyunca gerçekleştirilen tüm buluşlar, hem ekonomik hem de sosyal hayatı düzenli olarak ileriye taşımayı amaçlamıştır. 21. Yüzyılda bu değişimlerin en önemlisi kuşkusuz bilgi ve iletişim teknolojilerinin baş döndürücü gelişimidir. Bu gelişmeler hayatın her alanında olduğu gibi ekonomiyi ve finansal faaliyetleri de çok yakından etkilemiştir. İnternetin ilk adımlarının atıldığı 1950’li yıllardan bugüne, işletmeler dünyası çok sayıda teknolojik gelişime sahne olmuştur. Teknolojik gelişim ivmesinin bugün geldiği nokta yalnızca iş hayatına ilişkin değil, sosyal ve psikolojik boyutta davranış kalıplarımızda da deği...
Data Mining and Machine Learning in Cybersecurity
With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible
Finding Groups in Data
Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.
Statistical Models
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
Reinventing Public Service Communication
These essays address one of the most challenging debates in contemporary European media studies: the transition of the traditional Public Service Broadcasters into Public Service Media, as they widen their remit to produce and distribute public service content across more delivery platforms to meet the requirements of the digital age.
Ethical Issues in Journalism and the Media
This book examines the ethical concepts which lie at the heart of journalism, including freedom, democracy, truth, objectivity, honesty and privacy. The common concern of the authors is to promote ethical conduct in the practice of journalism, as well as the quality of the information that readers and audience receive from the media.
