Search Results for "fraud"
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Showing 8 open source projects for "fraud"
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Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Awesome Fraud Detection Research Papers
A curated list of data mining papers about fraud detection
A curated list of data mining papers about fraud detection from several conferences. -
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JumpServer
Manage assets on different clouds at the same time
...One system manages assets on different clouds at the same time. Audit recordings are stored in the cloud and will never be lost. One system, is used by multiple subsidiaries and departments at the same time. Prevent identity fraud and reuse. Prevent internal misuse and permission abuse. Management of people and assets. Retrospective safeguards and basis for accident analysis. -
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laravel-paystack
Laravel 6, 7, 8, 9, 10 and 11 Package for Paystack
...Developers love our thorough, well-documented APIs that let you to build everything from simple weekend projects to complex financial products serving hundreds of thousands of customers. If you can imagine it, you can build it with Paystack. Paystack’s combination of automated and manual fraud systems protects you from fraudulent transactions and associated chargeback claims. Understand your customers’ purchase patterns and do easy reconciliations with a robust data Dashboard and easy exports. -
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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tirreno
Open-source security framework for devs and product teams
tirreno is an open-source security framework. tirreno [tir.ˈrɛ.no] helps understand, monitor, and protect your product from threats, fraud, and abuse. While classic cybersecurity focuses on infrastructure and network perimeter, most breaches occur through compromised accounts and application logic abuse that bypasses firewalls, SIEM, WAFs, and other defenses. tirreno detects threats where they actually happen: inside your product. tirreno is a few-dependency, "low-tech" PHP/PostgreSQL application. ... -
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pH7 Social Dating CMS (pH7Builder)❤️
🚀 Professional Social Dating Web App Builder (formerly pH7CMS)
pH7Builder is a Professional, Free & Open Source PHP Social Dating Builder Software (primarily designed for developers ...). This Social Dating Web App is fully coded in object-oriented PHP (OOP) with the MVC pattern (Model-View-Controller). It is low resource-intensive, extremely powerful and highly secure. pH7Builder is included with over 42 native modules and is based on its homemade pH7 Framework which includes more than 52 packages To summarize, pH7Builder Social Dating Script... -
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations.
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