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Assumptions in Regression: Why, What, and How

“Garbage in, garbage out” defines the importance of data in data science or machine learning in a nutshell. Incorrect input will yield meaningless results and screening data ensures we get comprehensible results. Before we start building models and generating insights, we need to ensure that the quality of the data we are working with is […]