Training

Training in the context of data science and artificial intelligence refers to the process of using a dataset to teach a machine learning model to make accurate predictions or classifications. This involves selecting an appropriate algorithm, preparing the data, and iteratively adjusting the model's parameters until it achieves the desired level of accuracy. The goal of training is to create a model that can generalize well to new, unseen data. This is typically done by splitting the dataset into training and testing sets, and using the testing set to evaluate the model's performance. In some cases, additional techniques such as cross-validation or regularization may be used to improve the model's performance or prevent overfitting.
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