Pipeline

In Data Science, a pipeline refers to a sequence of data processing components that are assembled together to execute a specific task. A pipeline consists of multiple stages, where each stage performs a specific operation on the data and passes the output to the next stage. The input data is transformed and manipulated at each stage until the final output is produced. Pipelines are commonly used in machine learning workflows to automate the process of data preparation, feature extraction, model training, and prediction. They allow for efficient and reproducible experimentation, as well as easy deployment of the trained models. Pipelines can also be used for data cleaning, data integration, and data analysis tasks.
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