apply(risk) 2023 | Powering ML Fraud Detection Models With Advanced Aggregations скачать в хорошем качестве

apply(risk) 2023 | Powering ML Fraud Detection Models With Advanced Aggregations

apply(risk) 2023 | Powering ML Fraud Detection Models With Advanced Aggregations by: Mike Del Balso, Co-Founder & CEO, Tecton ML models are an essential tool in combating fraud. They can improve fraud detection rates, reduce false positives, and be re-trained to identify new fraudulent behavior as fraudsters adapt. However, fraud models require high-quality data that can be difficult to process and serve in production. Features typically require aggregations on streaming and real-time data, which are complex to build, compute intensive, and difficult to process at low latency. In this talk, Mike will walk through a sample use case and show how aggregations are typically processed. He’ll then show how feature engineering frameworks, like the one offered by Tecton, can simplify the development of these features. He’ll explain how these frameworks are orchestrated under the hood to process data at less than 1 second, serve data with less than 10ms latency, reduce processing costs, while ensuring consistency of offline and online data to improve model accuracy. apply(): The ML data engineering Conference Presented by Tecton Connect with us: Slack: https://slack.feast.dev/ LinkedIn:   / tectonai   Twitter:   / tectonai