Deep Learning with R
Deep Learning with R
Syllabus
Schedule
Readings
Code
Classes
Class sessions
Day 1: Fundamentals of Deep Learning I
Day 2: Fundamentals of Deep Learning II
Day 3: Overfitting, regularization, dropout, pretrained models, word embedding
Day 4: Convolutional Neural Networks, images
Day 5: Generative Adversarial Networks, Autoencoders, Recurrent Neural Networks, LSTM, GRU, sequence learning
Final project
Class details
Class-specific material will be posted following each class session
Cite
×