Companies investing in ML need to deliver models that improve over time with confidence, continuously! The only way that will happen is to spend less time slogging through data prep and more time building better ML features.
After talking with 100's of data scientists across every major industry, we put together this guide to ensure you're not neglecting crucial best practices in your data science projects. This is a FREE 8-point feature engineering best practices guide to creating a scalable, consistent model dataset directly in your Cloud Data Warehouse. Following this checklist will set you up for success on your next data science project. Share it with the team or keep it for yourself and impress your colleagues with your newfound knowledge, up to you.
