Gradient Descent §

Group: 4 #group-4

Relations §

• Neural Networks: Gradient descent is an optimization algorithm used to update the weights of a neural network during training to minimize the loss function.
• Activation Functions: The choice of activation function affects the performance of gradient descent optimization in neural networks.
• Convolutional Neural Networks: Gradient Descent optimization algorithms are used to update weights during training
• Optimization Algorithms: Gradient descent is an iterative optimization algorithm used to find the minimum of a function by moving in the direction of the negative gradient.
• Backpropagation: Backpropagation is a specific implementation of the gradient descent optimization algorithm for neural networks.
• Deep Learning: Gradient descent is an optimization algorithm used to update the weights of deep neural networks during training.