How Rocket Companies modernized their data science solution on AWS
In this post, we share how we modernized Rocket Companies’ data science solution on AWS to increase the speed to delivery from eight weeks to under one hour, improve operational…
AWS Glue
Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark
In this post, we will explore building a reusable RAG data pipeline on LangChain—an open source framework for building applications based on LLMs—and integrating it with AWS Glue and Amazon…
Harness the power of AI and ML using Splunk and Amazon SageMaker Canvas
For organizations looking beyond the use of out-of-the-box Splunk AI/ML features, this post explores how Amazon SageMaker Canvas, a no-code ML development service, can be used in conjunction with data…
Build a robust text-to-SQL solution generating complex queries, self-correcting, and querying diverse data sources
Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is…
Streamlining ETL data processing at Talent.com with Amazon SageMaker | Amazon Web Services
This post outlines the ETL pipeline we developed for feature processing for training and deploying a job recommender model at Talent.com. Our pipeline uses SageMaker Processing jobs for efficient data…
Visualize an Amazon Comprehend analysis with a word cloud in Amazon QuickSight | Amazon Web Services
Searching for insights in a repository of free-form text documents can be like finding a needle in a haystack. A traditional approach might be to use word counting or other…