- Analyzing Scientific Articles with fine-tuned SciBERT NER Model and Neo4j - Dec 9, 2021.
In this article, we will be analyzing a dataset of scientific abstracts using the Neo4j Graph database and a fine-tuned SciBERT model.
BERT, Graph Analytics, Neo4j, NLP, Python, Research
- The Difficulty of Graph Anonymisation - Feb 25, 2021.
Lessons from network science and the difficulty of graph anonymization. A data scientist's take on the difficultly of striking a balance between privacy and utility in anonymizing connected data.
Anonymized, Data Science, Graph Analytics, Graphs, Privacy, Singapore
- Fraud through the eyes of a machine - Nov 24, 2020.
Data structured as a network of relationships can be modeled as a graph, which can then help extract insights into the data through machine learning and rule-based approaches. While these graph representations provide a natural interface to transactional data for humans to appreciate, caution and context must be applied when leveraging machine-based interpretations of these connections.
Fraud, Fraud Detection, Graph Analytics, Machine Learning
- Lynx Analytics is open-sourcing LynxKite, its Complete Graph Data Science Platform - Jun 25, 2020.
Check out this article for a brief summary on what LynxKite is, where it is coming from and how it can help with your data science projects.
Data Science Platform, Graph Analytics, Open Source
- Graph Machine Learning Meets UX: An uncharted love affair - Jan 13, 2020.
When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.
Data Science, Data Visualization, Design, Graph Analytics, Machine Learning, UI/UX
- Scalable graph machine learning: a mountain we can climb? - Dec 10, 2019.
Graph machine learning is a developing area of research that brings many complexities. One challenge that both fascinates and infuriates those working with graph algorithms is — scalability. We take a close look at scalability for graph machine learning methods covering what it is, what makes it difficult, and an example of a method that tackles it head-on.
Deep Learning, Graph Analytics, Graph Databases, Machine Learning, Scalability
10 Free Top Notch Machine Learning Courses - Dec 6, 2019.
Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.
Books, Computer Vision, Courses, Deep Learning, Explainability, Graph Analytics, Interpretability, Machine Learning, NLP, Python
- Can graph machine learning identify hate speech in online social networks? - Sep 11, 2019.
Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network.
Graph Analytics, Machine Learning, Social Network Analysis, Twitter
Knowing Your Neighbours: Machine Learning on Graphs - Aug 8, 2019.
Graph Machine Learning uses the network structure of the underlying data to improve predictive outcomes. Learn how to use this modern machine learning method to solve challenges with connected data.
Convolutional Neural Networks, Graph Analytics, Graph Mining, Machine Learning
- Machine Learning and Deep Link Graph Analytics: A Powerful Combination - Apr 23, 2019.
We investigate how graphs can help machine learning and how they are related to deep link graph analytics for Big Data.
Fraud Detection, Graph Analytics, Graph Databases, Machine Learning, XAI
Graphs Are The Next Frontier In Data Science - Oct 18, 2018.
GraphConnect 2018, Neo4j’s bi-annual conference, was held in New York City in mid-September. Read about what happened, and why graphs are the next big thing in data science.
Conference, Data Science, Graph Analytics, Neo4j
- Modern Graph Query Language – GSQL - Jun 29, 2018.
This post introduces the prospect of fulfilling the need for a modern graph query language with GSQL
Graph Analytics, Graph Databases, SQL, TigerGraph
- Graph Analytics Using Big Data - Dec 4, 2017.
An overview and a small tutorial showing how to analyze a dataset using Apache Spark, graphframes, and Java.
Pages: 1 2
Apache Spark, Big Data, Graph Analytics, India, Java
- Introducing GraphFrames, a Graph Processing Library for Apache Spark - Mar 7, 2016.
An overview of Spark's new GraphFrames, a graph processing library based on DataFrames, built in a collaboration between Databricks, UC Berkeley's AMPLab, and MIT.
Apache Spark, Databricks, Graph Analytics
- Interactive Network and Graph Data Repository - Oct 17, 2014.
The network repository currently hosts over 500+ graphs/networks that span 19 collections of graphs from social science, machine learning, scientific computing, and many others.
Datasets, Graph Analytics, Graph Visualization, Network Graph
