Mathematical Problems in Data Science,Theoretical and Practical Methods Pdf This book describes current issues in data science and Big Data. For unsolved issues such as incomplete data relation and reconstruction, the publication incorporates potential solutions and statistical and computational procedures for data analysis. Initial chapters focus on investigating the properties of imperfect data collections and partial-connectedness among data points or data collections. Discussions also pay for the conclusion issue of Netflix matrix; machine learning procedure on massive data collections; image segmentation and movie search.
This publication contains three parts. The first part investigates the fundamental tools of data science. It features basic graph theoretical procedures, statistical and AI techniques for massive data collections. The next part, chapters focus on the procedural treatment of data science issues including machine learning procedures, mathematical image and video processing, topological data analysis, and statistical procedures. The final section offers case studies on special topics in variational learning, manifold learning, company and financial data retrieval, geometric search, and calculating models. Mathematical Issues in Data Science is a valuable source for researchers and professionals working on data engineering, information systems and networks. Advanced-level pupils studying computer engineering, electrical engineering and mathematics may also discover the material helpful.
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