AWS Machine Learning Blog

Category: Artificial Intelligence

Improve the return on your marketing investments with intelligent user segmentation in Amazon Personalize

Today, we’re excited to announce intelligent user segmentation powered by machine learning (ML) in Amazon Personalize, a new way to deliver personalized experiences to your users and run more effective campaigns through your marketing channels. Traditionally, user segmentation depends on demographic or psychographic information to sort users into predefined audiences. More advanced techniques look to […]

Amazon Personalize announces recommenders optimized for Retail and Media & Entertainment

Today, we’re excited to announce the launch of personalized recommenders in Amazon Personalize that are optimized for retail and media and entertainment, making it even easier to personalize your websites, apps, and marketing campaigns. With this launch, we have drawn on Amazon’s rich experience creating unique personalized user experiences using machine learning (ML) to build […]

Build MLOps workflows with Amazon SageMaker projects, GitLab, and GitLab pipelines

Machine learning operations (MLOps) are key to effectively transition from an experimentation phase to production. The practice provides you the ability to create a repeatable mechanism to build, train, deploy, and manage machine learning models. To quickly adopt MLOps, you often require capabilities that use your existing toolsets and expertise. Projects in Amazon SageMaker give […]

Bring Your Amazon SageMaker model into Amazon Redshift for remote inference

Amazon Redshift, a fast, fully managed, widely used cloud data warehouse, natively integrates with Amazon SageMaker for machine learning (ML). Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Data analysts and database developers want to use this data to train ML models, which […]

Run distributed hyperparameter and neural architecture tuning jobs with Syne Tune

Today we announce the general availability of Syne Tune, an open-source Python library for large-scale distributed hyperparameter and neural architecture optimization. It provides implementations of several state-of-the-art global optimizers, such as Bayesian optimization, Hyperband, and population-based training. Additionally, it supports constrained and multi-objective optimization, and allows you to bring your own global optimization algorithm. With […]

Your guide to AI and ML at AWS re:Invent 2021

It’s almost here! Only 9 days until AWS re:Invent 2021, and we’re very excited to share some highlights you might enjoy this year. The AI/ML team has been working hard to serve up some amazing content and this year, we have more session types for you to enjoy. Back in person, we now have chalk […]

AWS AI/ML Community attendee guides to AWS re:Invent 2021

The AWS AI/ML Community has compiled a series of session guides to AWS re:Invent 2021 to help you get the most out of re:Invent this year. They covered four distinct categories relevant to AI/ML. With a number of our guide authors attending re:Invent virtually, you will find a balance between virtually accessible sessions and sessions […]

Understand drivers that influence your forecasts with explainability impact scores in Amazon Forecast

We’re excited to launch explainability impact scores in Amazon Forecast, which help you understand the factors that impact your forecasts for specific items and time durations of interest. Forecast is a managed service for developers that uses machine learning (ML) to generate more accurate demand forecasts, without requiring any ML experience. To increase forecast model […]

New Amazon Forecast API that creates up to 40% more accurate forecasts and provides explainability

We’re excited to announce a new forecasting API for Amazon Forecast that generates up to 40% more accurate forecasts and helps you understand which factors, such as price, holidays, weather, or item category, are most influencing your forecasts. Forecast uses machine learning (ML) to generate more accurate demand forecasts, without requiring any ML experience. Forecast […]

Next Gen Stats Decision Guide: Predicting fourth-down conversion

It is fourth-and-one on the Texans’ 36-yard line with 3:21 remaining on the clock in a tie game. Should the Colts’ head coach Frank Reich send out kicker Rodrigo Blankenship to attempt a 54-yard field goal or rely on his offense to convert a first down? Frank chose to go for it, leading to a […]