Kubernetes, The Open and Scalable Approach to ML Pipelines

Still waiting for ML training to be over? Tired of running experiments manually? Not sure how to reproduce results? Wasting too much of your time on devops and data wrangling?

It’s okay if you’re a hobbyist, but data science models are meant to be incorporated into real business applications. Businesses won’t invest in data science if they don’t see a positive ROI. This calls for the adoption of an “engineered” approach — otherwise it is no more than a glorified science project with data...

Continue reading Yaron's post on Towards Data Science.