Lectures related to Relationship to Neural Learning Rules

Related lectures (32)

Explores neural networks, hidden layers, weight adjustments, activation functions, and the universal approximation theorem.

Introduces Convolutional Neural Networks, explaining their architecture, training process, and applications in semantic segmentation tasks.