Generative Data Intelligence

Tag: Amazon S3

Implementing Amazon Forecast in the retail industry: A journey from POC to production

Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time-series forecasts. Recently, based on...

Real-time analysis of customer sentiment using AWS

Companies that sell products or services online need to constantly monitor customer reviews left on their website after purchasing a product. The company’s marketing...

Generate cold start forecasts for products with no historical data using Amazon Forecast, now up to 45% more accurate

Now with Amazon Forecast, you can generate up to 45% more accurate forecasts for products with no historical data. Forecast is a managed service...

Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming...

Large-scale feature engineering with sensitive data protection using AWS Glue interactive sessions and Amazon SageMaker Studio

Organizations are using machine learning (ML) and AI services to enhance customer experience, reduce operational cost, and unlock new possibilities to improve business outcomes....

Build a cross-account MLOps workflow using the Amazon SageMaker model registry

A well-designed CI/CD pipeline is essential to scale any software development workflow effectively. When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to...

Enabling hybrid ML workflows on Amazon EKS and Amazon SageMaker with one-click Kubeflow on AWS deployment

Today, many AWS customers are building enterprise-ready machine learning (ML) platforms on Amazon Elastic Kubernetes Service (Amazon EKS) using Kubeflow on AWS (an AWS-specific...

Malware detection and classification with Amazon Rekognition

According to an article by Cybersecurity Ventures, the damage caused by Ransomware (a type of malware that can block users from accessing their data...

Detect multicollinearity, target leakage, and feature correlation with Amazon SageMaker Data Wrangler

In machine learning (ML), data quality has direct impact on model quality. This is why data scientists and data engineers spend significant amount of...

Run machine learning inference workloads on AWS Graviton-based instances with Amazon SageMaker

Today, we are launching Amazon SageMaker inference on AWS Graviton to enable you to take advantage of the price, performance, and efficiency benefits that...

Brain tumor segmentation at scale using AWS Inferentia

Medical imaging is an important tool for the diagnosis and localization of disease. Over the past decade, collections of medical images have grown rapidly,...

Run inference at scale for OpenFold, a PyTorch-based protein folding ML model, using Amazon EKS

This post was co-written with Sachin Kadyan, a leading developer of OpenFold. In drug discovery, understanding the 3D structure of proteins is key to assessing the ability of a drug to bind to it, directly impacting its efficacy. Predicting the 3D protein form, however, is very complex, challenging, expensive, and time consuming, and can take […]

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