Graphs

Learn how to use the NetworkX package to visualize complex networksPhoto by Alina Grubnyak on UnsplashA network graph is a form of visualization that enables you to visualize and analyze the relationships between entities. For example, the following figure shows the contribution of Wikipedia editors to the various Wikipedia language versions during one month in the summer of 2013.Source: https://en.wikipedia.org/wiki/Graph_theory#/media/File:Wikipedia_multilingual_network_graph_July_2013.svgFrom the network graph, you can…

Learn how to make your network graphs come to lifePhoto by DeepMind on UnsplashIn my previous article on creating network graphs, I showed how you can build one using the NetworkX package. The key problem with NetworkX is that the graph generated is static. Once the graph is plotted, there is no way the user is able to interact with it (such as rearrange the nodes, etc). The network graph would be more intuitive (and fun!) if the user can interact with it. And so this is the main focus of this article.In this article, I…

DiagrammeR , grViz()Photo by Lukas: https://www.pexels.com/photo/person-holding-blue-pen-590014/DiagrammeR is a package in R that is used to create graphs, and flowcharts using graphviz and mermaid.In this article, let’s look at how to create graphs using the grViz() in the DiagrammeR package.What is DiagrammeR?What is grViz()?How to create nodes, edges, labels, and their substitution and connection using grViz()?How to knit to HTML?DiagrammeR is a package within htmlwidgets for R. It is used to generate graphs using…

Bar charts and line graphs are both designed to help us visualize data. They are tools to convert numerical information into pictorial narratives that can be more easily comprehended. They don't change the data; they simply represent it.They do represent it in different ways, however, and even those slight differences can be enough to bias us as we try to make predictions, according to a new study.Researchers from the UK recruited more than 4,000 subjects over the internet, presented them with various graphs depicting…

Combine various NLP techniques to construct a knowledge graph representing your websiteA website is a reflection of the company. For the most part, it is used to inform users about various products and services and drive sales. However, the website grows and changes over time and many minor and major changes are introduced. As a result, it is not uncommon to end up with a disorganized website that fails to accomplish its original mission. Therefore, it makes sense to regularly evaluate the structure and content of the…

A Python Guide to Quickly Generate Knowledge GraphsPhoto by DeepMind on Unsplash.Knowledge graphs enable us to comprehend how different points of knowledge relate, giving us an extensive understanding of a field or topic. These graphs help us to discern how individual pieces of knowledge come together to form the larger picture. Clearly, constructing and visualising knowledge graphs can be an effective approach to many fields.In this article, we describe a process to generate new knowledge graphs by leveraging the largest…

Graph analysis, interactive visualizations, and graph machine learningPreview. Image by AuthorA graph is a relatively old mathematical data entity that is a set of connected elements. Since the graph is a very flexible structure and allows you to store information in a form familiar and convenient to humans, graphs have always been used in computer science and technology. With the raise of machine learning and deep learning, graphs have gained even more popularity by creating the field of graph machine learning.In this…

Photo by Clarisse Croset on UnsplashIn this post, I want to present discrete graph node embeddings as part of my series on machine learning on graphs (part 1, part 2, part 3). In particular, it also discusses my last research paper on discrete node embeddings which was recently accepted for presentation at AAAI 23, the premier conference on artificial intelligence.In a previous post, I presented the main ideas behind algorithms for learning node embeddings. By default, when we talk about word embeddings in natural…

Data Science in Archaeology, Part IThe archaeology of data (image by author).I’ve occasionally been asked, especially since I decided to go “all in” by getting another graduate degree , what data science has to do with archaeology . This will be the first of a short series of articles to demonstrate how I’ve been using data, statistics, and such to gain insights into what is a surprisingly convoluted area of research. Basically, while many data scientists are trying to make inferences about the present or future, I’ve…

How to generate interactive Directed Acyclic Graphs to visualise and understand causal inference models in 1 line of Python codePhoto by 愚木混株 cdd20 on UnsplashBackgroundCausal Inference is very topical at the moment and causal models are starting to become very useful additions to more traditional regression, classification and prediction models.Increasingly customers want to be able to visualise and understand the underlying causes and effects behind model predictions to help answer “Why?”, “What if?” and “What next?”…