Abstract
The chapter discusses the basics of big data analytics and the features of using analytical models in the field of process safety and risk management. The definition and basic principles of data analytics are necessary to understand the analytical techniques. The requirements for input data and the properties of analytical models are important for effective analytics. The concept, basic components, and varieties of machine learning are discussed. We consider such basic machine learning algorithms as clustering, classification, and regression. As advanced methods of data analytics, time series analysis methods, text analysis, and image analysis are proposed. Examples of the application of data analytics for risk management in the framework of process safety are considered.
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