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@@ -558,6 +558,7 @@ An updated and curated list of readings to illustrate best practices and pattern
 	* [Big Data Processing (2 parts) at Spotify](https://labs.spotify.com/2017/10/23/big-data-processing-at-spotify-the-road-to-scio-part-2/)
 	* [Big Data Processing at Uber](https://cdn.oreillystatic.com/en/assets/1/event/160/Big%20data%20processing%20with%20Hadoop%20and%20Spark%2C%20the%20Uber%20way%20Presentation.pdf)
 	* [Analytics Pipeline at Lyft](https://cdn.oreillystatic.com/en/assets/1/event/269/Lyft_s%20analytics%20pipeline_%20From%20Redshift%20to%20Apache%20Hive%20and%20Presto%20Presentation.pdf)
+	* [ML Data Pipelines for Real-Time Fraud Prevention at PayPal](https://www.infoq.com/presentations/paypal-ml-fraud-prevention-2018)
 	* [Big Data Analytics and ML Techniques at LinkedIn](https://cdn.oreillystatic.com/en/assets/1/event/269/Big%20data%20analytics%20and%20machine%20learning%20techniques%20to%20drive%20and%20grow%20business%20Presentation%201.pdf)
 	* [Self-Serve Reporting Platform on Hadoop at LinkedIn](https://cdn.oreillystatic.com/en/assets/1/event/137/Building%20a%20self-serve%20real-time%20reporting%20platform%20at%20LinkedIn%20Presentation%201.pdf)
 	* [Analytics Platform for Tracking Item Availability at Walmart](https://medium.com/walmartlabs/how-we-build-a-robust-analytics-platform-using-spark-kafka-and-cassandra-lambda-architecture-70c2d1bc8981)