I recently changed industries and joined a startup company where I’m responsible for building up a data science discipline. While we already had a solid data pipeline in place when I joined, we didn’t have processes in place for reproducible analysis, scaling up models, and performing experiments.
The goal of this series of blog posts is to provide an overview of how to build a data science platform from scratch for a startup, providing real examples using Google Cloud Platform (GCP) that readers can try out themselves. This series is intended for data scientists and analysts that want to move beyond the model training stage, and build data pipelines and data products that can be impactful for an organization.
Author: Ben Weber