Elephant(s) in the room: Graph neural networks, embeddings, and foundation models in spatial data science
Explores the application of Graph Neural Networks, embeddings, and foundation models to spatial data science, with practical examples in R.
Explores the application of Graph Neural Networks, embeddings, and foundation models to spatial data science, with practical examples in R.
A recap of the RecSys 2022 conference, highlighting key trends, favorite papers, and lessons learned in recommendation systems.
Explores improving recommender systems using graph-based methods and NLP techniques like word2vec and DeepWalk in PyTorch.
Explains how Graph Neural Networks and node2vec use graph structure and random walks to generate embeddings for machine learning tasks.