optimizers

the software engineer used an optimizer to improve the model's performance.

we need a robust optimizer for training deep neural networks.

the optimizer adjusted the learning rate during training.

choosing the right optimizer is crucial for successful machine learning.

the team compared several optimizers to find the best one.

gradient descent is a common optimization algorithm used as an optimizer.

the optimizer minimized the loss function effectively.

we fine-tuned the optimizer's hyperparameters for better results.

the optimizer’s convergence rate was significantly improved.

an adaptive optimizer can adjust to different data distributions.

the optimizer’s settings were carefully configured for optimal training.