Last updated: 4 months ago
Machine learning is one of the hot new areas in computer science. At the online retailer I work for, we use ML and big data every day to create better experiences for our customers. However, this data might not always be production ready out of the box. ML models need to be retrained, and data might have to be altered before production use.
This talk will showcase a few internal applications we've built to help aggregate, alter and increase the quality of our data, while also improving our ML training pipeline. Next to this we'll answer the big question 'Is Swift ready for production use?'.