- How Data Analytics Can Assist in Fraud Detection - Nov 11, 2019.
A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies.
- Using GRAKN.AI to Detect Patterns in Credit Fraud Data - Aug 30, 2017.
The term Horn Clause Mining, similar to Rule Based Machine Learning or Inductive Logic Programming, is used to describe the inverse of this functionality. Given a large enough knowledge base, can we infer rules that describe the data accurately?
- Top KDnuggets tweets, Sep 21-27: What is the #Blockchain and Why is it So Important? Watch #StrataHadoop #NYC Keynotes Live Sep 28-29 - Sep 28, 2016.
Top #DataScientists to follow on Twitter: @geoff_hinton @ylecun @SebastianThrun; What is the #Blockchain and Why is it So Important? The (Not So) New Data Scientist Venn Diagram; 9 Key #DeepLearning Papers, Explained.
- How to combat financial fraud by using big data? - Mar 25, 2016.
Financial fraud methods are becoming more sophisticated and the techniques to combat such attacks also need to evolve. Big data has brought with it novel fraud detection and prevention techniques such as behavioral analysis and real-time detection to give fraud fighting techniques a new perspective.
- KDnuggets™ News 15:n29, Sep 2: How to become a Data Scientist for Free; Big Data Out, Machine Learning In - Sep 2, 2015.
How to become a Data Scientist for Free; Gartner 2015 Hype Cycle: Big Data is Out, Machine Learning is In; KDnuggets part-time internship in Data Science, Data Journalism; The one language a Data Scientist must master.
- How Deep Learning Analytics Mimic the Mind - Mar 19, 2014.
There has been a lot of buzz surrounding the potential impact deep learning will have in the field of analytics. This post looks at the origins of deep learning.
- FICO: 20+ Years of Analytics Innovations to fight Fraud - Mar 12, 2014.
FICO infographic shows 20+ years of analytics innovations protecting consumers from payments fraud. It highlights the most significant innovations in anti-fraud analytics for card payments, and offers interesting facts about payment fraud.