Explores neural networks optimization, including backpropagation, batch normalization, weight initialization, and hyperparameter search strategies.
Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.
Explores neural networks, hidden layers, weight adjustments, activation functions, and the universal approximation theorem.
Covers the importance of preventive maintenance for pavement distress detection and introduces machine learning concepts for engineers.
Explores neural quantum states and their representation using artificial neural networks.
