Few-click segmentation mask labeling in Amazon SageMaker Ground Truth Plus

Amazon SageMaker Ground Truth Plus is a managed data labeling service that makes it easy to label data for machine learning (ML) applications. One common use case is semantic segmentation, which is a computer vision ML technique that involves assigning class labels to individual pixels in an image. For example, in video frames captured by … Read more

Accelerate time to insight with Amazon SageMaker Data Wrangler and the power of Apache Hive

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio. Data Wrangler enables you to access data from a wide variety of popular sources (Amazon S3, Amazon Athena, Amazon Redshift, Amazon EMR and Snowflake) and over 40 other third-party sources. … Read more

Real-time fraud detection using AWS serverless and machine learning services

Online fraud has a widespread impact on businesses and requires an effective end-to-end strategy to detect and prevent new account fraud and account takeovers, and stop suspicious payment transactions. Detecting fraud closer to the time of fraud occurrence is key to the success of a fraud detection and prevention system. The system should be able … Read more

Architect personalized generative AI SaaS applications on Amazon SageMaker

The AI landscape is being reshaped by the rise of generative models capable of synthesizing high-quality data, such as text, images, music, and videos. The course toward democratization of AI helped to further popularize generative AI following the open-source releases for such foundation model families as BERT, T5, GPT, CLIP and, most recently, Stable Diffusion. … Read more

Use a data-centric approach to minimize the amount of data required to train Amazon SageMaker models

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements. Applying these techniques allows ML practitioners … Read more

Use Snowflake as a data source to train ML models with Amazon SageMaker

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. Sagemaker provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so … Read more

How Marubeni is optimizing market decisions using AWS machine learning and analytics

This post is co-authored with Hernan Figueroa, Sr. Manager Data Science at Marubeni Power International. Marubeni Power International Inc (MPII) owns and invests in power business platforms in the Americas. An important vertical for MPII is asset management for renewable energy and energy storage assets, which are critical to reduce the carbon intensity of our … Read more

Portfolio optimization through multidimensional action optimization using Amazon SageMaker RL

Reinforcement learning (RL) encompasses a class of machine learning (ML) techniques that can be used to solve sequential decision-making problems. RL techniques have found widespread applications in numerous domains, including financial services, autonomous navigation, industrial control, and e-commerce. The objective of an RL problem is to train an agent that, given an observation from its … Read more