Approach to Fraud Detection: Neo4j Graph Data Science

The current anti-fraud strategies fail to identify all fraud incidents, but graph databases can help. In this article, we leverage Neo4j to spot suspicious accounts with PaySim Dataset to illustrate how to detect potential first-party financial fraudsters.

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Applying Data Science in Finance: Neo4j with GDS and ML for Financial Fraud Detection

Compared to traditional databases, Neo4j is intuitive, simple and understandable to non-technical users. In this workshop, you will learn how to detect first-party financial fraud using Neo4j, and leverage graph algorithms and machine learning for fraud prediction.

Azure DevOps Tutorial: Building CI/CD Pipelines & Versioning with Azure DevOps

Agile version control is a must to ensure a smooth software delivery process. In this tutorial, you will learn hands-on DevOps practices using Azure DevOps Pipeline & Release to facilitate continuous integration and delivery.

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TPIU Article

Newly Html Image Loading

This is an introduction to five HTML image loading techniques including lazy loading, AVIF and more that helps you optimize the web performance, which can have a great impact on user experience.

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Source: TPIsoftware University

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Using Neo4j Graph Database to Analyze Twitter Data

Graph data science provides valuable insights into complex information and data connections. This article walks you through the steps on how to analyze Twitter data using Neo4j graph database.

Source: Towards Data Science.

Written by Mananai Saengsuwan

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TPIsoftware Jan 2022 Newsletter

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