Multilayer Perceptron: Training and Optimization

This lecture covers the multilayer perceptron (MLP) model, training algorithm, data preprocessing, bag of words, histograms, noisy data cleaning, data normalization, activation functions, backpropagation, gradient-based learning, stochastic gradient descent, momentum, adaptive learning rate, gradient vanishing, weight initialization, regularization, and optimization techniques.