Computational and Statistical Methods for Analysing Big Data with Applications

Download Computational and Statistical Methods for Analysing Big Data with Applications PDF EPUB

Because of the level and complexity of data pieces currently being gathered in areas such as for example health, transportation, environmental technology, engineering, it, business and finance, contemporary quantitative analysts would like improved and suitable computational and statistical solutions to explore, model and attract inferences from big data. This publication aims to introduce appropriate methods for such endeavours, offering applications and case research for the intended purpose of demonstration.

Computational and Statistical Options for Analysing Big Data with Applications begins with a synopsis of the period of big data.

• Advanced computational and statistical methodologies for analysing big data are created
• Experimental style methodologies are referred to and implemented to help make the evaluation of big data even more computationally tractable
• Case research are discussed to show the execution of the developed strategies
• Five high-impact regions of program are studied: computer eyesight, geosciences, commerce, health care and transport
• Processing code/programs are given where suitable

See also

• Elementary Differential Equations (8th Edition)
• Student Solutions Manual for Elementary Differential Equations
• Elementary Differential Equations with Boundary Value Problems (2nd Edition) (Kohler/Johnson)