Real-time Point-of-Sale Analytics With a Data Lakehouse
Disruptions in the supply chain – from reduced product supply and diminished warehouse capacity – coupled with rapidly shifting consumer expectations for seamless...
Announcing Databricks Autologging for Automated ML Experiment Tracking
Machine learning teams require the ability to reproduce and explain their results--whether for regulatory, debugging or other purposes. This means every production model...
Improving On-Shelf Availability for Items With AI Out of Stock Modeling
This post was written in collaboration with Databricks partner Tredence. We thank Rich Williams, Vice President Data Engineering, and Morgan Seybert, Chief Business...
Solution Accelerator: Multi-touch Attribution
Behind the growth of every consumer-facing product is the acquisition and retention of an engaged user base. When it comes to customer acquisition...
How We Built Databricks on Google Kubernetes Engine (GKE)
Our release of Databricks on Google Cloud Platform (GCP) was a major milestone toward a unified data, analytics and AI platform that is...
An Experimentation Pipeline for Extracting Topics From Text Data Using PySpark
This post is part of a series of posts on topic modeling. Topic modeling is the process of extracting topics from a set...
The Delta Between ML Today and Efficient ML Tomorrow
Delta Lake and MLflow both come up frequently in conversation but often as two entirely separate products. This blog will focus on the...
Monitoring ML Models With Model Assertions
This is a guest post from the Stanford University Computer Science Department. We thank Daniel Kang, Deepti Raghavan and Peter Bailis of Stanford...
AML Solutions at Scale Using Databricks Lakehouse Platform
Anti-Money Laundering (AML) compliance has been undoubtedly one of the top agenda items for regulators providing oversight of financial institutions across the globe...
Feature Engineering at Scale
Feature engineering is one of the most important and time-consuming steps of the machine learning process. Data scientists and analysts often find themselves...