How We Used Databricks, MLeap, and Kubernetes to Productionize Spark ML Faster

This talk will describes how Autotrader, the UK’s leading digital automotive marketplace aunched their new “Days to Sell” ML-powered metric, using Databricks notebooks to experiment with and tune their model, MLeap to serve out predictions in real time, and Kubernetes to automate the deployment of new models. Edward Kent a Senior Developer at Autotrader shows show how they went from model experimentation and design, right through to deploying their model to a production environment. 

Links

« Detecting Mobile Malware with Apache Spark The Evolution of the Fashion Retail Industry in the Age of AI »