# Python or R for implementing machine learning algorithms for fraud detection [closed]

I was wondering which language can I use: R or Python, for my internship in fraud detection in an online banking system: I have to build machine learning algorithms (NN, etc.) that predict transaction frauds. Thank you very much for your answer.

I would say that it is your call and purely depends on your comfort with (or desire to learn) the language. Both languages have extensive ecosystems of packages/libraries, including some, which could be used for fraud detection. I would consider anomaly detection as the main theme for the topic. Therefore, the following resources illustrate the variety of approaches, methods and tools for the task in each ecosystem.

Python Ecosystem

• scikit-learn library: for example, see this page;
• LSAnomaly, a Python module, improving OneClassSVM (a drop-in replacement): see this page;
• Skyline: an open source example of implementation, see its GitHub repo;
• A relevant discussion on StackOverflow;
• pyculiarity, a Python port of Twitter's AnomalyDetection R Package (as mentioned in 2nd bullet of R Ecosystem below "Twitter's Anomaly Detection package").

R Ecosystem