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Experience Google Cloud Next 25
Uncover data's hidden connections using graph analytics in BigQuery. This session shows how to use BigQuery's scalable infrastructure for graph analysis directly in your data warehouse. Identify patterns, connections, and influences for fraud detection, drug discovery, social network analysis, and recommendation engines. Join us to explore the latest innovations in graphs and see real-world examples. Transform your data into actionable insights with BigQuery's powerful graph capabilities.
What are the Different Types of Graphs? The Most Common Misconceptions and Understanding Their Applications - Enterprise Knowledge
Learn about different types of graphs and their applications in data management and AI, as well as common misconceptions, in this article by Lulit Tesfaye.
Self-Organizing Graph Reasoning Evolves into a Critical State for Continuous Discovery Through Structural-Semantic Dynamics
Deep stuff! We uncovered a startling link between #entropy, a bedrock concept in #physics, and how #AI can discover new ideas without stagnating. In an era… | 41 comments on LinkedIn
GitHub - apache/incubator-hugegraph: A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)
A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends) - apache/incubator-hugegraph
Graph technologies outlook in 2025
Ashley Faith hosted Amy Hodler and me on a recent episode about “2025 Predictions” — here are notes I prepared, to review in 2026…
The Evolution of Intelligent Recommendations with Agentic Graph Systems
The Evolution of Intelligent Recommendations with Agentic Graph Systems ➿ Agentic graph systems for recommendation represent a sophisticated fusion of…
The Evolution of Intelligent Recommendations with Agentic Graph Systems
A Roadmap to Graph Analytics
why graphs would be superior to using Python for agents
Graph is increasingly driving the Agentic space, which I see as being a very good sign. Recently, a programmer asked why graphs would be superior to using…
why graphs would be superior to using Python
A New Era of Graph-Based Security Accelerated by AI | LinkedIn
At Microsoft, we strive to constantly learn and share our insights across innovation, culture and governance. Today, as we reflect on our progress since launching the Secure Future Initiative one year ago, I want to share a little more about our vision for a graph-powered platform future.
network analytics tools
As I did my PhD in network and data science, graphs are really close to me. Now, if you would like to get a tast of why these fields are so exciting and…
network analytics tools
Causal discovery with panel data
Causal discovery with panel data? Welcome tigramite Python package. (Note that I am still unsure about causal discovery applications.) I can't find who…
Causal discovery with panel data?
Data Object Graph (DOG), queryable, adaptable traversable hybrid data and execution graphs built for AI and traditional analytics use-cases in complex business processes
From DAGs to DOGs: Data Object Graph (DOG), queryable, adaptable traversable hybrid data and execution graphs built for AI and traditional analytics use-cases… | 59 comments on LinkedIn
Data Object Graph (DOG), queryable, adaptable traversable hybrid data and execution graphs built for AI and traditional analytics use-cases in complex business processes
Unlock the Power of Causal Graphs: Go Beyond Explainability with PyWhy
🌐 Unlock the Power of Causal Graphs: Go Beyond Explainability with PyWhy! Hey, #GraphGeeks! Don’t miss Amy Hodler and Michelle Yi’s session at Open Data…
Unlock the Power of Causal Graphs: Go Beyond Explainability with PyWhy
Financial Crime and Corruption Network Motifs
In this series of posts I make an appeal to organize global financial institutions and RiskTech vendors to collaborate on an open-source repository of financial risk patterns called network motifs to…
Graph theory
I work with graphs every day. This simple question left me speechless. During a meeting with a customer I started a sentence saying "In graph theory this… | 28 comments on LinkedIn
What is the path in this supply chain that leads to the least CO2 emissions?
If you care about sustainability, I have a data challenge to pull your hair out. What is the path in this supply chain that leads to the least CO2 emissions?…
What is the path in this supply chain that leads to the least CO2 emissions?
graphgeeks-lab/awesome-graph-universe: A curated list of resources for graph-related topics, including graph databases, analytics and science
A curated list of resources for graph-related topics, including graph databases, analytics and science - graphgeeks-lab/awesome-graph-universe
Awesome Graph Universe 🌐
Welcome to Awesome Graph Universe, a curated list of resources, tools, libraries, and applications for working with graphs and networks. This repository covers everything from Graph Databases and Knowledge Graphs to Graph Analytics, Graph Computing, and beyond.
Graphs and networks are essential in fields like data science, knowledge representation, machine learning, and computational biology. Our goal is to provide a comprehensive resource that helps researchers, developers, and enthusiasts explore and utilize graph-based technologies.
Feel free to contribute by submitting pull requests! 🚀
Simplifying Complex Graphs with Nested Nodes and Edges
Simplifying Complex Graphs with Nested Nodes and Edges: A Challenge Navigating massive graphs with nested nodes, including groups within groups, can feel like… | 34 comments on LinkedIn
Simplifying Complex Graphs with Nested Nodes and Edges
Tools for Advancing Analytic Tradecraft
Intelligence analysis utilizing Esri’s analytical, graph, and motion imagery capabilities, all within the same workflow.
Episode #212: Digging Into Graph Theory in Python With David Amos – The Real Python Podcast
Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he's been up to and share his knowledge about graph theory in Python.
Graph-Powered Analytics And Machine Learning With TigerGraph
Graph-Powered Analytics And Machine Learning With TigerGraph - Driving Business Outcomes with Connected Data
Interactive Network Graphs for Uncovering Complex Multicollinearity
Interactive Network Graphs for Uncovering Complex Multicollinearity 🕸️ Visualize multicollinearity in large datasets with interactive network graphs using… | 18 comments on LinkedIn
Interactive Network Graphs for Uncovering Complex Multicollinearity
Neo4j-Databricks Connector Delivers Deeper Insights, Faster GenAI Development - Graph Database & Analytics
Explore how using Neo4j Graph Database and Databricks together can deliver groundbreaking analytics and GenAI outcomes.
GraphGeeks Talk Ep6: RDF vs Property Graphs: Ask Me Anything
Graphs are changing the way we model, store, and query complex data. But when it comes to choosing the right type of graph model, the decision often boils do...
The nature of complex networks book
— Sergey Dorogovtsev (@dorogovtsev)
Static Graph Approximations of Dynamic Contact Networks for Epidemic Forecasting
Excited to share that our recent work "Static Graph Approximations of Dynamic Contact Networks for Epidemic Forecasting" is published at Scientific Reports…
Static Graph Approximations of Dynamic Contact Networks for Epidemic Forecasting
Working with Graphs: Pre-training and Application
Latest findings in pre-training graphs and using them for link recommendation
IDJC ElectionGraph Project - IDJC – Syracuse University
Research on misinformation origins in social media posts and advertising for the 2024 presidential election.
BELKA competition on Kaggle:
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