DevOps perspective to Machine Learning

Building a platform to continuously collaborate, learn, improve and deliver intelligence (or models) with data scientists A large global financial institution that we’ve been working with has had customer interaction data for the past couple of decades. They’ve been working on harnessing this data and unleashing learnings from it to improve efficiency but their current manual process for development and approvals takes 2-3 years to get a machine learning model released. What came next is Data-Science-Dev-Ops. This is the process of collaborating with Data Scientists to continuously learn, improve and deliver machine learning models to production and help visualize and streamline the value stream for this process. Join us as we share our journey through the process of delivering machine learning models to production in under 10 minutes in a highly regulated environment.