After covering the basics of GNN and PyG , now let’s start doing the actual implementation of GNN model training and inference. In this post we will use Cora citation dataset, where each node is a paper and edges refer to the citation. There seven types of papers (Example: Paper of DL, RL, Graphs) which…
In the last two posts the very basics and inner working of the GNN has been covered. Now we will start with the implementation of GNN with the help of pytorch geometric. In case you are not familiar with the working of pytorch please through my previous tutorial series of Deep Learning with Pytorch.In this…
In the previous post we talked about the basics of Graphs , adjacency matrix and why representation of Graph data and using the same for Machine Learning tasks are different than other forms of data. In this post I will try to explain the very basic Message Passing technique used in Graph Neural Networks. In…
In this new blog post series we will talk about Graph neural network which is according to the ‘State of AI report 2021’ has been stated as one of the hottest field of the AI research. This blog post series will be mostly implementation oriented , however required theory will be covered as much as…