Categories
Deep Learning

Short Introduction to Knowledge Graphs

Knowledge graphs are useful for providing structured sources of information for many downstream tasks. Hence, it is an interesting problem to build large knowledge graphs (KG) from a large text corpus. Being able to learn a KG from web-scale corpora means that we could leverage the large amount of unstructured information on websites (e.g. TechCrunch) and build structured knowledge bases. At a large scale, a KG is hard to maintain as it is not easy to keep track of issues like fact coverage, freshness and correctness. This blog post serves as a short introduction to the techniques used in building a simple KG.

Categories
Deep Learning

Transformer Architecture

This post provides a primer on the Transformer model architecture. It is extremely adept at sequence modelling tasks such as language modelling, where the elements in the sequences exhibit temporal correlations with each other.