Chaining
Chaining is a technique in data science and artificial intelligence that involves linking together multiple operations or models to form a pipeline. This pipeline allows for the seamless flow of data between each operation, with the output of one operation serving as the input for the next. Chaining is commonly used in machine learning workflows, where multiple models are trained and evaluated in sequence to achieve a desired outcome. By chaining together multiple models, data scientists can create more complex and accurate models that are capable of handling a wider range of tasks. Chaining can also be used to preprocess data before it is fed into a model, allowing for more efficient and effective training. Overall, chaining is a powerful technique that enables data scientists to build more sophisticated and accurate models.
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