- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- Mastering Advanced Analytics with Apache Spark - May 22, 2018.
Get ebook with a collection of the most popular technical blog posts that introduce you to machine learning on Apache Spark, and highlight many of the major developments around Spark MLlib and GraphX.
- Get Network insights in Excel with NodeXL - Dec 14, 2017.
NodeXL, the network overview discovery and exploration add-in for the familiar Microsoft Office Excel (TM) spreadsheet brings network functions within the reach of people who are more comfortable making pie charts than writing code. See what NodeXL finds in KDnuggets network and download NodeXL Pro for your analyses.
- 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.
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- Data Mining Panama Papers & Graph Analytics – Two Upcoming Webinars - May 16, 2016.
Ontotext offers a pair of free live webinars: Diving in Panama Papers and Open Data to Discover Emerging News, and GraphDB Fundamentals: Transforming your Graph Analytics with GraphDB. Reserve your spot today.
- Open Data with GraphDB & GraphDB Fundamentals – Upcoming Ontotext Webinars - Mar 17, 2016.
Get guidance through the gigantic sea of freely available Open Data and learn how it can empower you analysis (Mar 24) and learn how to use GraphDB to full potential and meet your analytics goals (Apr 7). Meet Ontotext in April in London or San Diego.
- 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.
- GraphDB Webinars from Ontotext: Data Visualization, Graph Analytics - Jan 25, 2016.
Two upcoming webinars show how to use the powerful GraphDB from Ontotext: Powerful Searches and Data Visualization in Graph Database (Jan 28) and Transforming your Graph Analytics with GraphDB (Feb 4). Check also GraphDB free version.
- Arabesque Distributed Graph Mining Platform - Nov 23, 2015.
Arabesque provides an elegant solution to the difficult problem of graph mining that lets a user easily express graph algorithms and efficiently distribute the computation.
- PNNL: Postdoc – Data Science (Knowledge Graphs and Machine Learning) - Oct 29, 2015.
This position is for a strongly motivated person with excellent skills in deep learning research and/or knowledge graph construction.
- Xerox Research Centre India: Research Scientist/Engineer: Text and Graph Analytics - Oct 5, 2015.
The team is working on challenging research problems with real life relevance pertaining to different business verticals such as Customer Care, Social Media, Healthcare, Transportation and Education.
- 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.
- LinkedIn Economic Graph Challenge - Oct 16, 2014.
Leverage the LinkedIn Economic Graph for your innovative and ambitious ideas for increasing economic value and gaining insights into economic opportunities using LinkedIn data and support. Proposals due Dec 15.
- Competition: Forecasting social network dynamic graph - Oct 6, 2014.
Forecast the creation and disruption of edges in social networks representing social platforms, mobile clients, or the research community. Competition runs until Nov 28.
- COMAD India Graph Mining Programming contest - Sep 23, 2014.
Compete in the graph mining programming competition at COMAD 2014 and apply your skills to finding subcommunities in networks. Registration deadline is October 15th, and code must be submitted by October 27th.
- Age homophily for predicting age of mobile phone customers - Sep 2, 2014.
Homophily (a tendency of people to associate with others like them) is ubiquitous in real world and in social networks. We show the existence of age homophily in a mobile phone communication network and exploit it to predict the age group for all users in the network.
- Big Data Innovation Summit 2014 Toronto: Day 2 Highlights - Aug 7, 2014.
Highlights from the presentations by Big Data leaders from Aviva, Canadian Imperial Bank, Royal College of Physicians and Surgeons of Canada, and University Health Network on day 2 of Big Data Innovation Summit 2014.
- GraphLab Create: large-scale machine learning platform for graph, structured, and text data - Jul 15, 2014.
GraphLab Create 1.0 brings large-scale machine learning capabilities to enterprises, and is the first to handle graph, structured, and text data in one platform.
- Upcoming Webcasts on Analytics, Big Data, Data Science – July 15 and beyond - Jul 14, 2014.
Hadoop, Data Curation, Text Mining, Driving business value with text analytics, SQL on Hadoop, Graph Analytics on Hadoop, Apache Spark, How Can Analytics Improve Business, and more.
- GraphLab Conference, Graph Analytics and Machine Learning, San Francisco July 21 - Jun 19, 2014.
GraphLab Conference (San Francisco, July 21) brings together experts in graph analytics, large scale machine learning, and data science from leading companies, academic institutions and organizations. Special KDnuggets discount.
- Interview: Conal Sathi, Data Scientist, Slice on Creating Value from Mining Shoppers’ e-Receipts - Jun 16, 2014.
We discuss the relevance of "Purchase Graph", Slice platform, analytical insights from mining all activity around a customer's purchase, experimentation strategy, experience of working as a data scientist and more.