Deep learning innovations and their convergence with big data
著者
書誌事項
Deep learning innovations and their convergence with big data
（Advances in data mining and database management (ADMDM) book series）（Premier reference source）
IGI Global, Information Science Reference, c2018
- : hardcover
大学図書館所蔵 全1件
注記
Includes bibliographical references (p. 200-255) and index
内容説明・目次
内容説明
The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics.
Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.
Contents include:
Deep Auto-Encoders
Deep Neural Network
Domain Adaptation Modeling
Multilayer Perceptron (MLP)
Natural Language Processing (NLP)
Restricted Boltzmann Machines (RBM)
Threat Detection
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