Leveraging Apache Spark for ML at scale and simplifying research to development.

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.

Maximo Gurmendez holds a master's degree in computer science/AI from Northeastern University, where he attended as a Fulbright Scholar. Since 2009, he has been working with dataxu, tackling the problem of ML for large datasets. He's also the Founder and Chief Engineer of Montevideo Labs (a data science and engineering consultancy). Additionally, Maximo is a computer science professor at the University of Montevideo and is director of its data science for business program. In 2019 Maximo co-wrote the book "Mastering Machine Learning on AWS" with Dr. Saket Mengle.