#SQL user-defined functions are now even more user-friendly and powerful Check out the enhancements we’ve made to keep queries simple while enjoying strong type-safety http://
bit.ly/3KWEBpD
@databricks
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SQL user-defined functions enhanced with better usability and type-safety
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Databricks Dolly: Open Source LLM Training in 30 Minutes
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Have 30 minutes to spare? That’s all you’ll need to train your own Dolly – an open source LLM – on Databricks and enjoy #ChatGPT-like capabilities. Check out our latest updates, including our GitHub repo, here https://
databricks.com/blog/2023/03/2
4/hello-dolly-democratizing-magic-chatgpt-open-models.html
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Migrating from Oracle to Databricks Lakehouse Architecture
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Does your current #data warehouse system struggle to quickly process and analyze data? Yes? Then it's time to migrate to #Lakehouse. Learn the steps to take when migrating from Oracle to Databricks https://
dbricks.co/3Io5NvA -
Databricks Kinesis Connector Powers Next-Generation Structured Streaming
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The next generation of Structured Streaming has entered the chat Learn how the Kinesis connector in Databricks Runtime can help you consolidate infrastructure into fewer streams – powering operational and ETL use cases https://
dbricks.co/3HfWU5u -
DataAISummit 2026: 250+ Technical Sessions on ML and Data
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Who else is excited for #DataAISummit? Join virtually or in San Francisco to dive into 250+ highly technical sessions on topics such as machine learning, analytics, security, data lakehouses and more. Register now https://
bit.ly/40bHaZr -
Ray 2.3.0 Brings ML Workloads to Databricks Spark
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Ray version 2.3.0 is coming in hot With the release, Ray workloads are now supported on Databricks and Spark standalone clusters, dramatically simplifying model development across both platforms. See how
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Databricks SQL Statement API Now Available in Public Preview
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Databricks #SQL Statement API is now in public preview Available on @AWS and @Azure
, users can now connect their #SQL warehouse to a REST API to access and manipulate #data managed by #Lakehouse. Learn more -
AutoML in Databricks: Creating ML Models with Hyperopt
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Using #AutoML to develop #ML models in Databricks is as easy as We’ll walk you through: Creating an AutoML experiment Starting AutoML Leveraging Hyperopt when developing ML models Watch now
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Databricks Notebooks Gets Major Editor Upgrade Features
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ICYMI: Databricks Notebooks just got an upgrade Updates include a new editor with faster autocomplete, Python code formatting, syntax highlighting, accelerated debugging, and more! Get the full rundown http://
bit.ly/3mz4tOk