Exploration


Exploration in Data Science refers to the process of discovering patterns, relationships, and insights in data through the use of various techniques such as data visualization, statistical analysis, and machine learning algorithms. It involves identifying and understanding the underlying structure of the data, as well as identifying any anomalies or outliers that may be present. The goal of exploration is to gain a deeper understanding of the data and to generate hypotheses that can be tested through further analysis. This process is often iterative, with new insights leading to further exploration and refinement of the analysis.


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