385: Advanced Data Topics and People-Centered Data Science
Super Data Science: ML & AI Podcast with Jon Krohn
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How to Build a Fraud Prevention Model
Caimings, Clustery and Naive Bayes are just some of the models used in fraud detection. Ensembling techniques such as XGBoost or target mean encoding can also be helpful. If you ensemble a group of different models together, you're likely to end up with a better result.
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