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The batch size is the number of examples used in each iteration of the training process. A larger batch size may provide faster progress but requires more memory and may not reach an optimal solution as quickly as desired. On the other hand, smaller batches offer better convergence and generalization rates. Ultimately, selecting a batch size depends on your available hardware as well as the specific problem being tackled. | The batch size is the number of examples used in each iteration of the training process. A larger batch size may provide faster progress but requires more memory and may not reach an optimal solution as quickly as desired. On the other hand, smaller batches offer better convergence and generalization rates. Ultimately, selecting a batch size depends on your available hardware as well as the specific problem being tackled. | ||
[[Category:Terms]] [[Category:Machine learning terms]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:not updated]] | ||