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[Deep Graph Learning] 4.1 Point, batch and mini-batch gradient descent

[Deep Graph Learning] 4.1 Point, batch and mini-batch gradient descent

[Deep Graph Learning] 4.4 GNN batch normalization layer

[Deep Graph Learning] 4.4 GNN batch normalization layer

Gradient Descent Optimizer Vs Stochastic Gradient Descent Optimizer | Optimizer in Deep Learning

Gradient Descent Optimizer Vs Stochastic Gradient Descent Optimizer | Optimizer in Deep Learning

[Deep Graph Learning] 4.2 Batching and GNN sampling methods

[Deep Graph Learning] 4.2 Batching and GNN sampling methods

Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.3 - Cluster GCN: Scaling up GNNs

Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.3 - Cluster GCN: Scaling up GNNs

Backpropagation, step-by-step | DL3

Backpropagation, step-by-step | DL3

GTN Training - Machine Learning - Deep Learning 1: Feedforward Neural Networks

GTN Training - Machine Learning - Deep Learning 1: Feedforward Neural Networks

Deep Neural Networks Video 8 - Backpropagation Algorithm

Deep Neural Networks Video 8 - Backpropagation Algorithm

[4c16] 05 - Deep FeedForward Neural Networks (part 2)

[4c16] 05 - Deep FeedForward Neural Networks (part 2)

Stanford CS224W: ML with Graphs | 2021 | Lecture 17.1 - Scaling up Graph Neural Networks

Stanford CS224W: ML with Graphs | 2021 | Lecture 17.1 - Scaling up Graph Neural Networks

Deep Learning Decal Fall 2017 Lecture 4: Optimization, Methodology, Applications

Deep Learning Decal Fall 2017 Lecture 4: Optimization, Methodology, Applications

9.1 Deep Networks Overview - Machine Learning Class 10-701

9.1 Deep Networks Overview - Machine Learning Class 10-701