Plurrrr

a tumblelog
Thu 07 May 2020

An Illustrated Guide to Graph Neural Networks

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.

What is Benford’s Law and why is it important for data science?

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.

A Guide to Big O notation

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.