Tuesday 16th June, 2015
4:30pm to 5:00pm
7 is a predictive analytics company focused on improving customer experience for Fortune 100 companies.We capture data about 2.5B customer interactions every year and we use this data to build machine learning models that predict the customer intent across multiple channels - online, voice and chat. In the past we used traditional tool set like R and SciKit and have been limited by their scale. We have chosen Spark Mllib to build an automated feature engineering and machine learning using Spark batch. We have also built a real time model evaluation system for experimentation using Spark streaming. This talk will cover our architecture, the challenges we faced and how we solved them and how we leverage Twitter's Algebird abstract algebra on top of Spark.
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