Machine Learning Model Training
Machine learning model training is the process of feeding a machine learning algorithm with data to enable it to learn and make predictions or decisions. The training process involves selecting the appropriate algorithm, preparing the data, splitting the data into training and testing sets, and optimizing the algorithm's parameters to achieve the best performance. During training, the algorithm adjusts its internal parameters to minimize the difference between its predicted output and the actual output. The goal of training is to create a model that can accurately predict outcomes for new, unseen data.
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