Iterative
Iterative refers to a process or approach that involves repeating a sequence of steps or actions until a desired outcome is achieved. In data science, iterative methods are commonly used in machine learning algorithms, where the model is trained on a dataset multiple times, with each iteration making small adjustments to the model's parameters to improve its accuracy. This process continues until the model reaches a satisfactory level of performance. Iterative methods are also used in data cleaning and preprocessing, where the data is repeatedly refined and transformed to improve its quality and usefulness for analysis. The iterative approach is often contrasted with the traditional waterfall approach, which involves completing each step of a project before moving on to the next, and may not allow for feedback or adjustments along the way.
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