An iterative optimization algorithm widely used in machine learning and deep learning applications to find the model parameters that correspond to the best fit between predicted and actual outputs.

• Machine learning
• Deep learning
• Neural networks
• Optimization algorithms

For instance, when training a neural network to classify images, SGD can be used to update the weights of the network based on a random subset of the training images, rather than the entire dataset.

• Designing the semantic data model