A gentle introduction to relational learning

When big data is really small Machine Learning for all, what does it mean to democratize AI? A simple example Resources 5 7. 7 The last 40 years have witnessed massive adoption of the relational model It's hard to find any examples today of enterprises whose data isn't in a relational database Millions of human hours invested in building relational models and populating them with data Relational databases are rich with knowledge of the underlying domains that they model The availability and accuracy of large amounts of curated data has made it possible for humans (BI) and machines (AI) to learn from the past and to predict the future The relational model dominates data management 8. When big data is small 9. 9 What would a database do? Features Entities 2. Feature extraction query s: Aggregates (statistics) generated from model spec and feature extraction query 3. Model specification (e.g., "degree 2 ridge regression") 1. Database ID x 1 x 2 x 3 ... y 10. 1 0 Supported methods include Linear regression Polynomial regression Factorization machines Decision trees Linear SVM K-Means & K-Median clustering Principal component analysis Deep sum-product networks (with more on the way) Does it work for all model classes or methods?