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Using Datawig, an AWS Deep Learning Library for Missing Value Imputation

KDnuggets

A lot of missing values in the dataset can affect the quality of prediction in the long run. Several methods can be used to fill the missing values and Datawig is one of the most efficient ones.

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AWS positioned in the Leaders category in the 2022 IDC MarketScape for APEJ AI Life-Cycle Software Tools and Platforms Vendor Assessment

AWS Machine Learning Blog

The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. The company had to be among the top 15 vendors by the reported revenues of 2020–2021 in the APEJ region, according to IDC’s AI Software Tracker. AWS position.

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How Kakao Games automates lifetime value prediction from game data using Amazon SageMaker and AWS Glue

AWS Machine Learning Blog

In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker. It was launched in June 2021 and has been ranked within the top three in revenue in Korea.

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Deploy large language models for a healthtech use case on Amazon SageMaker

AWS Machine Learning Blog

In 2021, the pharmaceutical industry generated $550 billion in US revenue. Traditional manual processing of adverse events is made challenging by the increasing amount of health data and costs. We implemented the solution using the AWS Cloud Development Kit (AWS CDK). As always, AWS welcomes your feedback.

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Implement real-time personalized recommendations using Amazon Personalize

AWS Machine Learning Blog

The post Architecting near real-time personalized recommendations with Amazon Personalize shows how to architect near real-time personalized recommendations using Amazon Personalize and AWS purpose-built data services. For this particular use case, you will be uploading interactions data and items data.

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Govern generative AI in the enterprise with Amazon SageMaker Canvas

AWS Machine Learning Blog

Launched in 2021, Amazon SageMaker Canvas is a visual point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without writing any code. This is crucial for compliance, security, and governance.

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Analyze Amazon SageMaker spend and determine cost optimization opportunities based on usage, Part 2: SageMaker notebooks and Studio

AWS Machine Learning Blog

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support offering. In Part 1 , we showed how to get started using AWS Cost Explorer to identify cost optimization opportunities in SageMaker. You can build custom queries to look up AWS CUR data using standard SQL.

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