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Using Apache Spark to Predict Installer Retention from Clickstream Data (Patrick Halina)

381 views · Published 27 September 2018 · 25:02 · Indexed 8 November 2026

Channel: Databricks · 2018 · Science & Technology

Patrick Halina is the tech lead of ML Engineering at Zynga, based out of the Toronto office.

At Zynga we’ve developed a technique to represent user game actions with temporal heatmap feature sets. Utilizing the power of PySpark, our generic data pipeline can generate thousands of features without the need to manually interpret the events of each game. The graphical structure of the heatmaps allow us to take advantage of established image classification techniques to make personalized user level predictions. Within 30 minutes of installing our games, Zynga is able to make accurate predictions on whether a new installer will churn or become a payer.

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Using Apache Spark to Predict Installer Retention from Clickstream Data (Patrick Halina)

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