Hands-on

Understanding Graphs with NetworkX
tl;dr: In this tutorial we discussed NetwokX library to deal with Graph data.
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Classification of Graph Data using Machine Learning Algorithm based on Graph features
tl;dr: In this tutorial we discussed how to do classification on Graph data using it's features.
[notes] [codes] [Video]

Node2Vec implimentation from scratch and classification of graph using node2vec generated embeddings.
tl;dr: In this tutorial we discussed how to implement Node2Vec from scratch using python and do classification on Graph data using generated embeddings from node2vec.
[notes] [codes] [Video]

Implementation of GCN and GAT using PyTorch (from scratch) and using PyTorch Geometric.
tl;dr: In this tutorial we discussed how to implement GAT and GCN from scratch using python, PyTorch and do classification on Graph data using generated embeddings from GAT and GCN.
[notes] [codes] [Video]

Transductive vs Inductive Learning on GNNs for Node Classification.
tl;dr: In this tutorial we discussed how to implement models for both inductive setting and transductive settings. We have discussed the differences in the performace of both the methods on correponding data settings.
[notes] [codes] [Video]

Link Prediction using GNNs (Transductive vs Inductive Learning)-Part_1.
tl;dr: In this tutorial we will first understand how we can slpit the given data for the link prediction task. Later on we will see how can we do link prediction on Cora Dataset.
[notes] [codes] [Video]

Hierarchical Graph Representation Learning with Differentiable Pooling.
tl;dr: In this tutorial, we will first understand the architecture of DiffPool and the overall graph classification model. Later on, we will see how can we do Graph Classification on ENZYME Dataset.
[notes] [codes] [Video]