AWS Machine Learning Blog

Tag: Amazon SageMaker

Predict types of machine failures with no-code machine learning using Amazon SageMaker Canvas

Predicting common machine failure types is critical in manufacturing industries. Given a set of characteristics of a product that is tied to a given type of failure, you can develop a model that can predict the failure type when you feed those attributes to a machine learning (ML) model. ML can help with insights, but […]

Demystifying machine learning at the edge through real use cases

October 2023: Starting in April 26th, 2024, you can no longer access Amazon SageMaker Edge Manager. For more information about continuing to deploy your models to edge devices, see SageMaker Edge Manager end of life. Edge is a term that refers to a location, far from the cloud or a big data center, where you […]

Architecture diagram

How InfoJobs (Adevinta) improves NLP model prediction performance with AWS Inferentia and Amazon SageMaker

This is a guest post co-written by Juan Francisco Fernandez, ML Engineer in Adevinta Spain, and AWS AI/ML Specialist Solutions Architects Antonio Rodriguez and João Moura. InfoJobs, a subsidiary company of the Adevinta group, provides the perfect match between candidates looking for their next job position and employers looking for the best hire for the […]

SageMaker Data Wrangler Risk Modeling

Build a mental health machine learning risk model using Amazon SageMaker Data Wrangler

This post is co-written by Shibangi Saha, Data Scientist, and Graciela Kravtzov, Co-Founder and CTO, of Equilibrium Point. Many individuals are experiencing new symptoms of mental illness, such as stress, anxiety, depression, substance use, and post-traumatic stress disorder (PTSD). According to Kaiser Family Foundation, about half of adults (47%) nationwide have reported negative mental health […]

Build, Share, Deploy: how business analysts and data scientists achieve faster time-to-market using no-code ML and Amazon SageMaker Canvas

April 2023: This post was reviewed and updated with Amazon SageMaker Canvas’s new features and UI changes. Machine learning (ML) helps organizations increase revenue, drive business growth, and reduce cost by optimizing core business functions across multiple verticals, such as demand forecasting, credit scoring, pricing, predicting customer churn, identifying next best offers, predicting late shipments, […]

create autopilot experiment

Make batch predictions with Amazon SageMaker Autopilot

Amazon SageMaker Autopilot is an automated machine learning (AutoML) solution that performs all the tasks you need to complete an end-to-end machine learning (ML) workflow. It explores and prepares your data, applies different algorithms to generate a model, and transparently provides model insights and explainability reports to help you interpret the results. Autopilot can also […]

season-trend decomposition

Prepare time series data with Amazon SageMaker Data Wrangler

Time series data is widely present in our lives. Stock prices, house prices, weather information, and sales data captured over time are just a few examples. As businesses increasingly look for new ways to gain meaningful insights from time-series data, the ability to visualize data and apply desired transformations are fundamental steps. However, time-series data […]

Building a customized recommender system in Amazon SageMaker

Recommender systems help you tailor customer experiences on online platforms. Amazon Personalize is an artificial intelligence and machine learning service that specializes in developing recommender system solutions. It automatically examines the data, performs feature and algorithm selection, optimizes the model based on your data, and deploys and hosts the model for real-time recommendation inference. However, […]

Accelerating innovation: How serverless machine learning on AWS powers F1 Insights

FORMULA 1 (F1) turns 70 years old in 2020 and is one of the few sports that combines real-time skill with engineering and technical prowess. Technology has always played a central role in F1; where the evolution of the rules and tools is built into the DNA of F1. This keeps fans engaged and drivers […]

Building an AI-powered Battlesnake with reinforcement learning on Amazon SageMaker

Battlesnake is an AI competition based on the traditional snake game in which multiple AI-powered snakes compete to be the last snake surviving. Battlesnake attracts a community of developers at all levels. Hundreds of snakes compete and rise up in the ranks in the online Battlesnake global arena. Battlesnake also hosts several offline events that […]