GraphML is an XML-based file format for graphs. The GraphML file format results from the joint effort of the graph drawing community to define a common format for exchanging graph structure data. It uses an XML-based syntax and supports the entire range of possible graph structure constellations including directed, undirected, mixed graphs, hypergraphs, and application-specific attributes. (Wikipedia).
Graph Theory: 02. Definition of a Graph
In this video we formally define what a graph is in Graph Theory and explain the concept with an example. In this introductory video, no previous knowledge of Graph Theory will be assumed. --An introduction to Graph Theory by Dr. Sarada Herke. This video is a remake of the "02. Definitio
From playlist Graph Theory part-1
What is a Graph? | Graph Theory
What is a graph? A graph theory graph, in particular, is the subject of discussion today. In graph theory, a graph is an ordered pair consisting of a vertex set, then an edge set. Graphs are often represented as diagrams, with dots representing vertices, and lines representing edges. Each
From playlist Graph Theory
Graph Theory FAQs: 01. More General Graph Definition
In video 02: Definition of a Graph, we defined a (simple) graph as a set of vertices together with a set of edges where the edges are 2-subsets of the vertex set. Notice that this definition does not allow for multiple edges or loops. In general on this channel, we have been discussing o
From playlist Graph Theory FAQs
What Is GraphQL? REST vs. GraphQL
To get better at system design, subscribe to our weekly newsletter: https://bit.ly/3tfAlYD Checkout our bestselling System Design Interview books: Volume 1: https://amzn.to/3Ou7gkd Volume 2: https://amzn.to/3HqGozy ABOUT US: Covering topics and trends in large-scale system design, from
From playlist Computer Science Fundamentals
Over the past few years GraphQL has gained much traction, but what’s the state of GraphQL in Python. This talk describes what GraphQL is, why it has been created and the current state of GraphQL libraries in Python. There will be a short history of GraphQL, some examples of what makes it
From playlist GraphQL
How to get started with Graph ML? (Blog walkthrough)
❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ In this video, I walk you through my blog on getting started with Graph ML. I talk about research, learning, cool Graph ML apps, resources to get you started, my GAT project, and beyond!
From playlist Graph Neural Nets
Semantic Parsing English to GraphQL | Andre Carerra | OpenAI Scholars Demo Day 2020
Learn more: https://openai.com/blog/openai-scholars-2020-final-projects#andre
From playlist Events and Talks
Unveiling the Power of Graphs: Node and Edge Classification w/ GraphSAGE | GraphML
Full code example of Node and Edge classification with GraphSAGE for GraphML. DGL on PyTorch backbone. Graph Neural Networks explained. One of the most popular and widely adopted tasks for graph neural networks is node classification, where each node in the training/validation/test set is
From playlist Node & Edge Classification, Link Prediction w/ GraphML
Uncover the Secrets of Graph Data: Train, Test and Validation GRAPH Datasets | GraphML PyG DGL
Short intro to splitting into Training data set, Validation data set and Test data set. Mistakes that happened to me when working with Graph data sets. #graphs #machinelearning #datasets
From playlist Node & Edge Classification, Link Prediction w/ GraphML
VISUAL Code: Graph LINK PREDICTION | How AI Recommender work | Graph ML
HOW does LINK PREDICTION work in recommender systems for graph neural networks? Is it the intelligent code in GRAPH ML? Or is the secret of node embedding and link prediction somewhere else? In the topological structure of the computational graph? Explore the secret of why link prediction
From playlist Node & Edge Classification, Link Prediction w/ GraphML
Graphing Equations By Plotting Points - Part 1
This video shows how to graph equations by plotting points. Part 1 of 2 http://www.mathispower4u.yolasite.com
From playlist Graphing Various Functions
Node Classification w/ GRAPH CONVOLUTIONAL Networks for GraphML
PyG coding example (on node classification) for GCN: A choice of convolutional NN architecture motivated via a localized first-order approximation of spectral graph convolutions. The GCN model scales linearly in the number of graph edges and learns hidden layer representations that encode
From playlist Node & Edge Classification, Link Prediction w/ GraphML
ETA Prediction with Graph Neural Networks in Google Maps | Paper Explained
👨👩👧👦 JOIN OUR DISCORD COMMUNITY: Discord ► https://discord.gg/peBrCpheKE 📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER: Substack ► https://aiepiphany.substack.com/ ❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany In this video I cover the "ETA Prediction with Gr
From playlist Graph Neural Nets
CODE: GRAPH Link Prediction w/ DGL on Pytorch and PyG Code Example | GraphML | GNN
For Graph ML we make a deep dive to code LINK Prediction on Graph Data sets with DGL and PyG. We examine the main ideas behind LINK Prediction and how to code a link prediction example in PyG and DGL - Deep Graph Library. DGL - Easy Deep Learning on Graphs with framework agnostic coding (e
From playlist Node & Edge Classification, Link Prediction w/ GraphML
DjangoCon US 2018 - Introduction to Django and GraphQL by Patrick Arminio
DjangoCon US 2018 - Introduction to Django and GraphQL by Patrick Arminio GraphQL has grown a lot overtime, but it seems to still be a new “thing” in the Python and Django World. This talk will be an introduction to GraphQL, explaining why it has been created and how you can use it in Pyt
From playlist DjangoCon US 2018
The Definition of a Graph (Graph Theory)
The Definition of a Graph (Graph Theory) mathispower4u.com
From playlist Graph Theory (Discrete Math)
AMMI Course "Geometric Deep Learning" - Lecture 12 (Applications & Conclusions) - Michael Bronstein
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July-August 2021 by Michael Bronstein (Imperial College/Twitter), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 12: What's next? • Beyond Mess
From playlist AMMI Geometric Deep Learning Course - First Edition (2021)
Graph Neural Networks - a perspective from the ground up
What is a graph, why Graph Neural Networks (GNNs), and what is the underlying math? Highly recommended videos that I watched many times while making this: Petar Veličković's GNN video → https://youtu.be/8owQBFAHw7E Michael Bronstein's Geometric Deep Learning keynote speech (beautiful!) →
From playlist Summer of Math Exposition Youtube Videos
Mathematical theories start with axioms, but penultimate to that is the definition. When we go to learn, what's the best definition to commit to memory? Here we talk about Graph Theory and I give you 3 definitions to choose from. Which would you use?
From playlist Summer of Math Exposition 2 videos
Unlocking the Potential of Message Passing: Exploring GraphSAGE, GCN and GAT | GNN GraphML
Introduction to GRAPH ML, Graph Neural Networks (GNN) and the main idea behind Message Passing in graph network configurations of GraphSAGE, GCN and GAT. Message passing applied to Graph Convolutional Networks (GCN), GraphSAGE and Graph Attention Networks. The key difference between GAT an
From playlist Learn Graph Neural Networks: code, examples and theory