What are some effective optimization techniques for AI models?

What are some effective optimization techniques for AI models?

Some effective optimization techniques include gradient descent, Adam optimizer, and learning rate scheduling.

Can you explain how gradient descent works?

Gradient descent is an iterative optimization algorithm that adjusts model parameters to minimize the loss function.

What is the difference between batch and stochastic gradient descent?

Batch gradient descent uses the entire dataset to compute gradients, while stochastic uses one sample at a time.

Are there any specific techniques for optimizing deep learning models?

Yes, techniques like dropout, batch normalization, and data augmentation are commonly used to optimize deep learning models.