______________ is a technique used in training neural networks where multiple models are trained and combined to improve performance and robustness

__________ is a regression technique that combines multiple weak models to create a strong model by weighting each model's prediction and summing them up.

In neural networks, ______________ normalization is applied to stabilize and speed up the training process.

networks, ______________ normalization is applied to stabilize and speed up the training process.

In a neural network, the layer is responsible for combining high-level features and making predictions.

The ______________ technique is used to adjust the weights in a neural network to minimize the cost function.