Achieve rapid time-to-value business outcomes with faster ML model training using Amazon SageMaker Canvas

Favorite Machine learning (ML) can help companies make better business decisions through advanced analytics. Companies across industries apply ML to use cases such as predicting customer churn, demand forecasting, credit scoring, predicting late shipments, and improving manufacturing quality. In this blog post, we’ll look at how Amazon SageMaker Canvas delivers faster and

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Shared by AWS Machine Learning March 4, 2023

Build a GNN-based real-time fraud detection solution using the Deep Graph Library without using external graph storage

Favorite Fraud detection is an important problem that has applications in financial services, social media, ecommerce, gaming, and other industries. This post presents an implementation of a fraud detection solution using the Relational Graph Convolutional Network (RGCN) model to predict the probability that a transaction is fraudulent through both the

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Shared by AWS Machine Learning March 1, 2023

Extract non-PHI data from Amazon HealthLake, reduce complexity, and increase cost efficiency with Amazon Athena and Amazon SageMaker Canvas

Favorite In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. It enables them to unlock the value of their data, identify trends, patterns, and predictions, and differentiate themselves from their competitors. For example, in the healthcare industry, ML-driven analytics can

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Shared by AWS Machine Learning March 1, 2023