Dataflowr
Videos about deep learning. Please visit https://www.dataflowr.com/ for more material.
Deep Learning on Graphs(3/3): Graph embedding
Deep Learning on Graphs(2/3): Signal processing on graphs
Deep Learning on Graphs(1/3): Node embedding
Basics of Deep Learning: Transfer Learning
Basics of Deep Learning: Resnets
Basics of Deep Learning: Batchnorm
Basics of Deep Learning: Dropout
Basics of Deep Learning: Problems with Depth
Basics of Deep Learning: Benefits of Depth
Basics of Deep Learning: Siamese Representation Learning
Pytorch tutorial on batch for sequences
Introduction to Julia: Automatic differentiation with dual numbers
Privacy Preserving Machine Learning by Daniel Huynh
Pytorch tutorial: Recurrent Neural Networks practice
Pytorch tutorial: Recurrent Neural Networks theory
Pytorch tutorial: Generative adversarial networks (GAN)
Pytorch tutorial: Autoencoders
Pytorch tutorial: Collaborative filtering
Pytorch tutorial: Embedding layers and dataloaders
Pytorch tutorial: Convolutional neural network
Pytorch tutorial: writing a PyTorch module
Pytorch tutorial: Optimization for deep leaning
Pytorch tutorial: Loss functions
Pytorch tutorial: PyTorch tensors
Pytorch tutorial: Introduction & Course Overview
Pytorch tutorial: automatic differentiation