Category: Artificial Intelligence

Machine learning (ML) administrators play a critical role in maintaining the security and integrity of ML workloads. Their primary focus is to ensure that users operate with the utmost security, adhering to the principle of least privilege. However, accommodating the diverse needs of different user personas and creating appropriate permission policies can sometimes impede agility. […]

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code. SageMaker Data Wrangler supports Snowflake, a popular […]

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. One of the main challenges can be deploying a well-performing, locally trained model to the cloud for inference and use in other applications. It can be cumbersome to manage the process, but with the right tool, […]

This post is co-written with Aruna Abeyakoon and Denisse Colin from Light and Wonder (L&W). Headquartered in Las Vegas, Light & Wonder, Inc. is the leading cross-platform global game company that provides gambling products and services. Working with AWS, Light & Wonder recently developed an industry-first secure solution, Light & Wonder Connect (LnW Connect), to […]

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. Lifecycle configurations are shell scripts triggered by Studio lifecycle events, such as starting […]

As a contact center agent, would you rather focus on having productive customer conversations or get distracted by having to look up customer information and knowledge articles that could exist in various systems? We’ve all been there. Having a productive conversation while multitasking is challenging. A single negative experience may put a dent on a […]

November 2023: This post was updated to include the Amazon SageMaker APIs. Amazon SageMaker Studio is a web-based integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. For provisioning Studio in your AWS account and Region, you first need to create an Amazon SageMaker […]

At SambaSafety, their mission is to promote safer communities by reducing risk through data insights. Since 1998, SambaSafety has been the leading North American provider of cloud–based mobility risk management software for organizations with commercial and non–commercial drivers. SambaSafety serves more than 15,000 global employers and insurance carriers with driver risk and compliance monitoring, online […]

Dive into Deep Learning (D2L.ai) is an open-source textbook that makes deep learning accessible to everyone. It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math. So far, D2L has been adopted by more than 400 universities around the world, such as […]

Every organization has its own set of standards and practices that provide security and governance for their AWS environment. Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. SageMaker provides a set of templates […]