Introduction to Graph Machine Learning: Basic Concepts

Introduction to Graph Machine Learning: Basic Concepts

Source: DeepHub IMBA This article is about 2600 words long and is recommended to be read in 5 minutes. This article will start from the basics to introduce what a graph is, how we describe and represent them, and what their properties are. Graph Machine Learning (Graph ML) is a branch of machine learning that … Read more

Practical Guide to Graph Neural Networks in TensorFlow

Practical Guide to Graph Neural Networks in TensorFlow

Source: ZHUAN ZHI This article serves as a tutorial and is recommended for a 5-minute read. This tutorial's practical section will be based on TF-GNN, a library for handling graph-structured data in TensorFlow. Graphs are universal data structures that can represent information from various domains (social, biomedical, online transactions, etc.). Graph Neural Networks (GNNs) are … Read more

Optimize Data Structures for Performance Improvement

Optimize Data Structures for Performance Improvement

Slow code execution is often due to poor data structure choices. A few days ago, I wrote a feature to handle user relationships, and it became painfully slow with large data volumes. While I was struggling with it, I tried the Cursor code analysis feature, and unexpectedly, it quickly identified the problem and taught me … Read more