In today’s economic climate, efficiency is key to maintaining a competitive edge for the organization. It is imperative to continue innovating, but escalating costs are becoming a greater and greater concern.
What if there was a way to make the entire AI lifecycle efficient and effective? A way to reuse existing components and share resources so that the enterprise can continuously roll out new AI services without costs spiraling out of control?
This is just what the data science team at Home Credit International (HCI) is doing. In this session, Jiri will be sharing enterprise secrets to establishing efficient systems for ML/AI (including building ML pipelines, leveraging a feature store for ML feature sharing and reuse, and automating the entire data science process to take repetitive manual work out of the equation).