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Detect fraudulent transactions using machine learning with Amazon SageMaker

Businesses can lose billions of dollars each year due to malicious users and fraudulent transactions. As more and more business operations move online, fraud and abuses in online systems are also on the rise. To combat online fraud, many businesses have been using rule-based fraud detection systems. However, traditional fraud detection systems rely on a …

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Implement RStudio on your AWS environment and access your data lake using AWS Lake Formation permissions

R is a popular analytic programming language used by data scientists and analysts to perform data processing, conduct statistical analyses, create data visualizations, and build machine learning (ML) models. RStudio, the integrated development environment for R, provides open-source tools and enterprise-ready professional software for teams to develop and share their work across their organization Building, …

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Design patterns for serial inference on Amazon SageMaker

As machine learning (ML) goes mainstream and gains wider adoption, ML-powered applications are becoming increasingly common to solve a range of complex business problems. The solution to these complex business problems often requires using multiple ML models. These models can be sequentially combined to perform various tasks, such as preprocessing, data transformation, model selection, inference …

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Run interactive pipelines at scale using Beam Notebooks

To all Apache Beam and Dataflow users: If you’ve experimented with Beam, prototyped a pipeline, or verified assumptions about a dataset, you might have used Beam Notebooks or other interactive alternatives such as Google Colab or Jupyter Notebooks. You might also have noticed a gap between running a small prototype pipeline in a notebook and …

How Tarteel Uses AI to Help Arabic Learners Perfect Their Pronunciation

There are some 1.8 billion Muslims, but only 16% or so of them speak Arabic, the language of the Quran. This is in part due to the fact that many Muslims struggle to find qualified instructors to give them feedback on their Quran recitation. Enter today’s guest and his company Tarteel, a member of the …

The Calibration Generalization Gap

This paper was accepted at the Workshop on Distribution-Free Uncertainty Quantification at ICML 2022. Calibration is a fundamental property of a good predictive model: it requires that the model predicts correctly in proportion to its confidence. Modern neural networks, however, provide no strong guarantees on their calibration— and can be either poorly calibrated or well-calibrated …

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

by Jun He, Akash Dwivedi, Natallia Dzenisenka, Snehal Chennuru, Praneeth Yenugutala, Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations. A large number of batch workflows run daily to serve various business needs. …

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Learning from CEOs: Collaboration and connectivity are keys to navigating sustainability

It’s the most frequently identified challenge CEOs expect to face over the next two to three years. It’s more vexing than regulation, cyber risk, and even supply chain disruptions. It’s sustainability, reveals IBM’s Institute for Business Value 2022 CEO Study “Own your impact: Practical pathways to transformational sustainability”. As pressures from a broad set of …

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Table Tennis: A Research Platform for Agile Robotics

Posted by Avi Singh, Research Scientist, and Laura Graesser, Research Engineer, Robotics at Google Robot learning has been applied to a wide range of challenging real world tasks, including dexterous manipulation, legged locomotion, and grasping. It is less common to see robot learning applied to dynamic, high-acceleration tasks requiring tight-loop human-robot interactions, such as table …

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Train a time series forecasting model faster with Amazon SageMaker Canvas Quick build

Today, Amazon SageMaker Canvas introduces the ability to use the Quick build feature with time series forecasting use cases. This allows you to train models and generate the associated explainability scores in under 20 minutes, at which point you can generate predictions on new, unseen data. Quick build training enables faster experimentation to understand how …