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SparkML: Easy ML Productization for Real-Time Bidding

SparkML: Easy ML Productization for Real-Time Bidding

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dataxu bids on ads in real-time on behalf of its customers at the rate of 3 million requests a second and trains on past bids to optimize for future bids. Our system trains thousands of advertiser-specific models and runs multi-terabyte datasets. In this presentation we will share the lessons learned from our transition towards a fully automated Spark-based machine learning system and how this has drastically reduced the time to get a research idea into production. We’ll also share how we: – continually ship models to production – train models in an unattended fashion with auto-tuning capabilities – tune and overbooked cluster resources for maximum performance – ported our previous ML solution into Spark – evaluate the performance of high-rate bidding models
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