AWS Machine Learning Blog

Category: SageMaker

Optimizing I/O for GPU performance tuning of deep learning training in Amazon SageMaker

GPUs can significantly speed up deep learning training, and have the potential to reduce training time from weeks to just hours. However, to fully benefit from the use of GPUs, you should consider the following aspects: Optimizing code to make sure that underlying hardware is fully utilized Using the latest high performant libraries and GPU […]

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Accelerating innovation: How serverless machine learning on AWS powers F1 Insights

FORMULA 1 (F1) turns 70 years old in 2020 and is one of the few sports that combines real-time skill with engineering and technical prowess. Technology has always played a central role in F1; where the evolution of the rules and tools is built into the DNA of F1. This keeps fans engaged and drivers […]

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Cisco uses Amazon SageMaker and Kubeflow to create a hybrid machine learning workflow

This is a guest post from members of Cisco’s AI/ML best practices team, including Technical Product Manager Elvira Dzhuraeva, Distinguished Engineer Debo Dutta, and Principal Engineer Amit Saha. Cisco is a large enterprise company that applies machine learning (ML) and artificial intelligence (AI) across many of its business units. The Cisco AI team in the […]

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How Euler Hermes detects typo squatting with Amazon SageMaker

This is a guest post from Euler Hermes. In their own words, “For over 100 years, Euler Hermes, the world leader in credit insurance, has accompanied its clients to provide simpler and safer digital products, thus becoming a key catalyzer in the world’s commerce.” Euler Hermes manages more than 600,000 B2B transactions per month and […]

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Building a visual search application with Amazon SageMaker and Amazon ES

Sometimes it’s hard to find the right words to describe what you’re looking for. As the adage goes, “A picture is worth a thousand words.” Often, it’s easier to show a physical example or image than to try to describe an item with words, especially when using a search engine to find what you’re looking […]

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Introducing the open-source Amazon SageMaker XGBoost algorithm container

XGBoost is a popular and efficient machine learning (ML) algorithm for regression and classification tasks on tabular datasets. It implements a technique known as gradient boosting on trees and performs remarkably well in ML competitions. Since its launch, Amazon SageMaker has supported XGBoost as a built-in managed algorithm. For more information, see Simplify machine learning […]

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The tech behind the Bundesliga Match Facts xGoals: How machine learning is driving data-driven insights in soccer

It’s quite common to be watching a soccer match and, when seeing a player score a goal, surmise how difficult scoring that goal was. Your opinions may be further confirmed if you’re watching the match on television and hear the broadcaster exclaim how hard it was for that shot to find the back of the […]

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Scheduling Jupyter notebooks on SageMaker ephemeral instances

It’s 5 PM on a Friday. You’ve spent all afternoon coding out a complex, sophisticated feature engineering strategy. It just started working on your Amazon SageMaker Studio t3.medium notebook, and all you want to do is plug this onto a massive instance, scale it out over the rest of your dataset, and go home. You […]

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Detecting fraud in heterogeneous networks using Amazon SageMaker and Deep Graph Library

Fraudulent users and malicious accounts can result in billions of dollars in lost revenue annually for businesses. Although many businesses use rule-based filters to prevent malicious activity in their systems, these filters are often brittle and may not capture the full range of malicious behavior. However, some solutions, such as graph techniques, are especially suited […]

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A/B Testing ML models in production using Amazon SageMaker

Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to quickly build, train, and deploy machine learning (ML) models. Tens of thousands of customers, including Intuit, Voodoo, ADP, Cerner, Dow Jones, and Thomson Reuters, use Amazon SageMaker to remove the heavy lifting from the ML process. With Amazon SageMaker, […]

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