Population

In Data Science, population refers to the entire set of individuals, objects, or events that we are interested in studying. It is the complete collection of all the elements that we want to analyze and draw conclusions about. In statistical analysis, we often use a sample of the population to make inferences about the entire population. The size of the population can vary depending on the research question and the scope of the study. In machine learning, population can refer to the set of all possible instances that the model can encounter during training or testing. The population can be finite or infinite, and it can be homogeneous or heterogeneous in terms of its characteristics.

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Environmental Impact: Environmental Impact refers to the effect of human activities on the environment. In the context of Data Science, it refers to the impact of data-related activities on the environment. The increasing use of technology and data has led to a ... Read More >>
Lazy Evaluation: Lazy evaluation is a programming technique where the evaluation of an expression is delayed until its value is actually needed. In other words, the computation is not performed until the result is required. This technique is used to improve ... Read More >>
NoSQL: NoSQL is a type of database management system that is not based on the traditional relational database model. Instead, NoSQL databases use a variety of data models, including document, key-value, column-family, and graph formats. NoSQL data ... Read More >>

Population

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