Lecture 13 | Generative Models Lecture 13 | Generative Models begin-post-stats Stanford University School of Engineering • 54K views end-post-stats begin-duration 1:17:41 end-duration Math topics: _Mathematical_optimization_##Mathematical optimization##_Maxima_and_minima_##Maxima and minima##_Mathematical_optimization_##Mathematical optimization##_Gradient_descent_##Gradient descent##_Probability_##Probability##_Bayes'_rule_##Bayes' rule##_Probability_##Probability##_Generative_model_##Generative model Other topics: _Machine_learning_##Machine learning##_Unsupervised_learning_##Unsupervised learning##_Machine_learning_##Machine learning##_Supervised_learning_##Supervised learning##_Dimensionality_reduction_##Dimensionality reduction##_Artificial_neural_networks_##Artificial neural networks##_Backpropagation_##Backpropagation##_Artificial_neural_network_##Artificial neural network##_Autoencoder_##Autoencoder##_Psychometrics_##Psychometrics##_Factor_analysis_##Factor analysis##_Sampling_(statistics)_##Sampling (statistics)##_Latent_variable_##Latent variable##_Data_##Data##_Test_set_##Test set##_Data_##Data##_Prior_probability_##Prior probability video-id: 5WoItGTWV54 channel_Stanford_University_School_of_Engineering_ So What Learning Artificial neural networks , Data , Machine learning , Mathematical optimization , Probability , Psychometrics Monday, January 22, 2018 Share Share