Remove 2010 Remove AWS Remove Clustering
article thumbnail

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning Blog

Make sure you have the following prerequisites: Create an S3 bucket Configure MongoDB Atlas cluster Create a free MongoDB Atlas cluster by following the instructions in Create a Cluster. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Note we have two folders.

article thumbnail

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Suppliers of data center GPUs include NVIDIA, AMD, Intel, and others.

AWS 96
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Unlock ML insights using the Amazon SageMaker Feature Store Feature Processor

AWS Machine Learning Blog

Prerequisites To follow this tutorial, you need the following: An AWS account. AWS Identity and Access Management (IAM) permissions. Spark provides distributed processing on clusters to handle data that is too big for a single machine. Prior to joining AWS, Ninad worked as a software developer for 12+ years.

ML 115
article thumbnail

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

Database 155
article thumbnail

Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

AI 77