Graph Deep Learning (GDL) is an up-and-coming area of study. It’s super useful when learning over and analysing graph data. Here, I’ll cover the basics of a simple Graph Neural Network (GNN) and the intuition behind its inner workings.
Source: An Illustrated Guide to Graph Neural Networks, an article by Rishabh Anand.
We discuss a little-known gem for data analytics — Benford’s law, which tells us about expected distribution of significant digits in a diverse set of naturally occurring datasets and how this can be used for anomaly or fraud detection in scientific or technical publications.
Source: What is Benford’s Law and why is it important for data science?, an article by Tirthajyoti Sarkar.
You have probably come across big O notation before. Maybe you have read that merge sort is better than insertion sort because merge sort is O(n log n) compared to insertion sort, which is O(n2). In this article, you'll understand what this means, and why this makes merge sort the better algorithm.
Source: A Guide to Big O notation, an article by Erik André Jakobsen.