GitHub

This is a combination version of the RAG and Fine tuning to train AI models efficiently

RAFT - Retrieval-Augmented Fine-Tuning - is a training methodology that teaches a language model how to reason over a specific, curated body of knowledge while deliberately ignoring distracting, ...

Databricks says it solved the decades-old data pipeline problem that's been slowing AI agents

Databricks says new products LTAP and Lakehouse//RT unify transactional and analytical data for AI agents, delivering sub-100ms latency and no ETL pipelines.

Databricks Now Powered by ZoomInfo's GTM.AI as the GTM Context Layer for Lakehouse AI

ZoomInfo's verified company, contact, and signal data now flows natively into the Databricks lakehouse through GTM.AI, so every model, score, ...

Monte Carlo Announces Integration with Agent Bricks, Bringing Cohesive Observability to Enterprise AI on Databricks

Monte Carlo, the agent trust platform for enterprise AI, today announced its support for Agent Bricks, Databricks' platform to build, deploy and govern AI agents on enterprise data. With this ...

Dun & Bradstreet brings agentic credit and portfolio management workflows to Databricks

Dun & Bradstreet announced it is delivering agentic credit and portfolio management workflows, leveraging the D&B Commercial Graph™, available through the Databricks Marketplace and Databricks ...
GitHub

README: Healthcare Data Analysis Incremental Load in Cassandra Using PySpark Project.md

I have this Healthcare Data Analysis Incremental Load in Cassandra Using PySpark Project This project is Healthcare Data Analysis with PySpark + Cassandra. The assignment requires daily CSV files, ...