AWS Machine Learning Blog

Category: Artificial Intelligence

Amazon SageMaker Notebook Instances now support configuring and restricting IMDS versions

Today, we’re excited to announce that Amazon SageMaker now supports the ability to configure Instance Metadata Service Version 2 (IMDSv2) for Notebook Instances, and for administrators to control the minimum version with which end-users create new Notebook Instances. You can now choose IMDSv2 only for your new and existing SageMaker Notebook Instances to take advantage […]

Reimagine search on GitHub repositories with the power of the Amazon Kendra GitHub connector

Amazon Kendra offers highly accurate semantic and natural language search powered by machine learning (ML). Many organizations use GitHub as a code hosting platform for version control and to redefine collaboration of open-source software projects. A GitHub account repository might include many content types, such as files, issues, issue comments, issue comment attachments, pull requests, […]

Merge cells and column headers in Amazon Textract tables

Financial documents such as bank, loan, or mortgage statements are often formatted to be visually appealing and easy to read for the human eye. These same features can also make automated processing challenging at times. For instance, in the following sample statement, merging rows or columns in a table helps reduce information redundancy, but it […]

Detect financial transaction fraud using a Graph Neural Network with Amazon SageMaker

Fraud plagues many online businesses and costs them billions of dollars each year. Financial fraud, counterfeit reviews, bot attacks, account takeovers, and spam are all examples of online fraud and malicious behaviors. Although many businesses take approaches to combat online fraud, these existing approaches can have severe limitations. First, many existing methods aren’t sophisticated or […]

Automate vending Amazon SageMaker notebooks with Amazon EventBridge and AWS Lambda

Having an environment capable of delivering Amazon SageMaker notebook instances quickly allows data scientists and business analysts to efficiently respond to organizational needs. Data is the lifeblood of an organization, and analyzing that data efficiently provides useful insights for businesses. A common issue that organizations encounter is creating an automated pattern that enables development teams […]

Run text classification with Amazon SageMaker JumpStart using TensorFlow Hub and Hugging Face models

July 2023: You can also use the newly launched JumpStart APIs, an extension of the SageMaker Python SDK. These APIs allow you to programmatically deploy and fine-tune a vast selection of JumpStart-supported pre-trained models on your own datasets. Please refer to Amazon SageMaker JumpStart models and algorithms now available via API for more details on how […]

Seamlessly connect Amazon Athena with Amazon Lookout for Metrics to detect anomalies

Amazon Lookout for Metrics is an AWS service that uses machine learning (ML) to automatically monitor the metrics that are most important to businesses with greater speed and accuracy. The service also makes it easier to diagnose the root cause of anomalies, such as unexpected dips in revenue, high rates of abandoned shopping carts, spikes […]

Detect social media fake news using graph machine learning with Amazon Neptune ML

In recent years, social media has become a common means for sharing and consuming news. However, the spread of misinformation and fake news on these platforms has posed a major challenge to the well-being of individuals and societies. Therefore, it is imperative that we develop robust and automated solutions for early detection of fake news […]

Optimize F1 aerodynamic geometries via Design of Experiments and machine learning

FORMULA 1 (F1) cars are the fastest regulated road-course racing vehicles in the world. Although these open-wheel automobiles are only 20–30 kilometers (or 12–18 miles) per-hour faster than top-of-the-line sports cars, they can speed around corners up to five times as fast due to the powerful aerodynamic downforce they create. Downforce is the vertical force […]

Build a risk management machine learning workflow on Amazon SageMaker with no code

Since the global financial crisis, risk management has taken a major role in shaping decision-making for banks, including predicting loan status for potential customers. This is often a data-intensive exercise that requires machine learning (ML). However, not all organizations have the data science resources and expertise to build a risk management ML workflow. Amazon SageMaker […]