Answer / Km.nicky

Model building is the process of creating a mathematical or computational model that can accurately predict outputs given inputs. In machine learning, this involves selecting an appropriate algorithm, training the model on a dataset, evaluating its performance, and fine-tuning it to improve its accuracy. Model building often requires careful selection of input features, handling of missing data, and regularization techniques to prevent overfitting. Cross-validation is commonly used for evaluating the performance of models.

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