Analyze Amazon SageMaker spend and determine cost optimization opportunities based on usage, Part 3: Processing and Data Wrangler jobs

Favorite In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. Since its introduction, we’ve helped hundreds of customers optimize their workloads, set guardrails, and improve the visibility of their machine learning (ML) workloads’ cost and usage. In this series of posts, we share

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Shared by AWS Machine Learning May 31, 2023

How OCX Cognition reduced ML model development time from weeks to days and model update time from days to real time using AWS Step Functions and Amazon SageMaker

Favorite This post was co-authored by Brian Curry (Founder and Head of Products at OCX Cognition) and Sandhya MN (Data Science Lead at InfoGain) OCX Cognition is a San Francisco Bay Area-based startup, offering a commercial B2B software as a service (SaaS) product called Spectrum AI. Spectrum AI is a

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Shared by AWS Machine Learning May 26, 2023

Get insights on your user’s search behavior from Amazon Kendra using an ML-powered serverless stack

Favorite Amazon Kendra is a highly accurate and intelligent search service that enables users to search unstructured and structured data using natural language processing (NLP) and advanced search algorithms. With Amazon Kendra, you can find relevant answers to your questions quickly, without sifting through documents. However, just enabling end-users to

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Shared by AWS Machine Learning May 26, 2023

Build a powerful question answering bot with Amazon SageMaker, Amazon OpenSearch Service, Streamlit, and LangChain

Favorite One of the most common applications of generative AI and large language models (LLMs) in an enterprise environment is answering questions based on the enterprise’s knowledge corpus. Amazon Lex provides the framework for building AI based chatbots. Pre-trained foundation models (FMs) perform well at natural language understanding (NLU) tasks

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Shared by AWS Machine Learning May 26, 2023