M11: Some learning methods for parameter estimation in PGMs
M10: Markov chain Monte Carlo methods for PGMs
M9: Introduction to Probabilistic Graphical Models
M8: Recurrent neural networks and LSTMs
M7: Visualizing what a CNN learns
M6: Why deep learning works
M5: Advanced CNNs for image recognition
M4: Simple improvements to CNNs
M3: Intro to convolutional neural networks
M2: Intro to neural networks
M1: Penalized and generalized linear models
M0: Course introduction
M10: Markov chain Monte Carlo methods for PGMs
M9: Introduction to Probabilistic Graphical Models
M8: Recurrent neural networks and LSTMs
M7: Visualizing what a CNN learns
M6: Why deep learning works
M5: Advanced CNNs for image recognition
M4: Simple improvements to CNNs
M3: Intro to convolutional neural networks
M2: Intro to neural networks
M1: Penalized and generalized linear models
M0: Course introduction