CSC601 Lecture Notes - Lecture 1: Feature Engineering, Predictive Analytics, Missing Data

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25 May 2023
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Unit 1: introduction to data analytics and life cycle: explain data analytics lifecycle. The data analytics lifecycle can be summarized into the following stages: discovery: this stage involves understanding the problem or question that needs to be addressed through data analytics. The organization defines its business goals and objectives, identifies key stakeholders, and determines the scope of the analytics project. Data sources are explored and assessed for their relevance and availability: data preparation: in this stage, data is collected from various sources and undergoes cleaning, integration, and transformation processes. Data quality is assessed, and missing values, outliers, or inconsistencies are addressed. The prepared data is then structured in a format suitable for analysis, ensuring it is accurate, complete, and properly formatted: model planning: in this stage, the analytical approach is determined. The appropriate methods, techniques, and algorithms are selected based on the nature of the problem and the available data.

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