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Unstructured data management and governance using AWS AI/ML and analytics services

Flipboard

After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. The solution integrates data in three tiers.

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How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

AWS Machine Learning Blog

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. This capability of predictive analytics, particularly the accurate forecast of product categories, has proven invaluable.

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Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions

AWS Machine Learning Blog

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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Apply fine-grained data access controls with AWS Lake Formation in Amazon SageMaker Data Wrangler

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure.

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10 Things AWS Can Do for Your SaaS Company

Smart Data Collective

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning Blog

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

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Demand forecasting at Getir built with Amazon Forecast

AWS Machine Learning Blog

Getir used Amazon Forecast , a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts, to increase revenue by four percent and reduce waste cost by 50 percent. He joined Getir in 2021, and has been working as a Data Scientist.