Big data analytics is the process of examining big data to uncover insights such as hidden patterns, correlations, market trends, and customer preferences that can help organizations make informed business decisions. It is a tool for collecting large volumes of information through the
predictive model analysis, statistical algorithms, and what-if analysis driven by analytics systems.
In this book presents some approaches to the development and applications of deep learning techniques and optimization strategies in Big Data Analytics. Through 17 masterfully exposed chapters, various topics related to this emerging field of knowledge are developed, showing everything from reviews of the state of the art to frontier applications in various areas such as medicine, engineering and the mathematical optimization of complex systems. The result of this proposal is an obligatory reference for engineers, mathematicians, statisticians and data science scientists due to the quality and timeliness of its content and the excellent presentation of the work by the publisher.
– Prof. Gilberto Pérez-Lechuga, University Autonomous of the Hidalgo State
The book is recommended as it provides a rich selection of recent advancements in big data analytics in the aspects of deep learning techniques and optimization strategies in terms of both algorithms and models, and also a wide range of application areas. Also, given the extent of experience that the authors have in the area, they have enriched the text with a lot of supplementing illustrations and applications.
– Dr. Jinal Parikh, Amrut Mody School of Management, Ahmedabad University, and Dr. Gerhard Wilhelm Weber, Poznan University of Technology, Poznan, Poland