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Databricks Assistant Tips & Tricks for Data Engineers

The generative AI revolution is transforming the way that teams work, and Databricks Assistant leverages the best of these advancements. It allows you...

Bringing the Lakehouse to R developers: Databricks Connect now available in sparklyr

We’re excited to announce that the latest release of sparklyr on CRAN introduces support for Databricks Connect . R users now have seamless...

Big Book of MLOps Updated for Generative AI

Last year, we published the Big Book of MLOps, outlining guiding principles, design considerations, and reference architectures for Machine Learning Operations (MLOps). Since...

Crossing Bridges: Reporting on NYC taxi data with RStudio and Databricks

As data enthusiasts, we love uncovering stories in datasets. With Posit's RStudio Desktop and Databricks, you can analyze data with dplyr, create impressive...

The 2023 State of Data + AI: How Businesses Are Preparing for the New Age of AI

The historic surge of interest in large language models (LLMs) since ChatGPT launched to the public late last year has made the topic...

Software Engineering Best Practices With Databricks Notebooks

June 25, 2022 by Rafi Kurlansik and Austin Ford in
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...