Software Engineering Best Practices With Databricks Notebooks
Notebooks are a popular way to start working with data quickly without configuring a complicated environment. Notebook authors can quickly go from interactive…
Architecting MLOps on the Lakehouse
Here at Databricks, we have helped thousands of customers put Machine Learning (ML) into production. Shell has over 160 active AI projects saving…
Managing Model Ensembles With MLflow
In machine learning, an ensemble is a collection of diverse models that provide more predictive power together than any single model would on…
Need for Data-centric ML Platforms
This blog is the first in a series on MLOps and Model Governance. The next blog will be by Joseph Bradley and will…
Optimizing User Defined Functions with Apache Spark™ and R in the Real World: Scaling Pitch Scenario Analysis with the Minnesota Twins Part 2
Introduction In part 1 we talked about how Baseball Operations for the Minnesota Twins wanted to run up to 20k simulations on 15…
How the Minnesota Twins Scaled Pitch Scenario Analysis to Measure Player Performance – Part 1
Statistical Analysis in the Game of Baseball A single pitch in Major League Baseball (MLB) generates tens of megabytes of data, from pitch…
