Category: Amazon SageMaker

With Amazon SageMaker Ground Truth, you can build highly accurate training datasets for machine learning quickly. SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, SageMaker Ground Truth can lower your labeling costs by up to 70% using automatic labeling, […]

Keras is a popular and well-documented open source library for deep learning, while Amazon SageMaker provides you with easy tools to train and optimize machine learning models. Until now, you had to build a custom container to use both, but Keras is now part of the built-in TensorFlow environments for TensorFlow and Apache MXNet. Not […]

Nomura Research Institute (NRI) is a leading global provider of system solutions and consulting services in Japan and an APN Premium Consulting Partner. NRI is increasingly getting requests to help customers optimize inventory and production plans, reduce costs, and create better customer experiences. To address these demands, NRI is turning to new sources of data, specifically […]

Pioneer Corp is a Japanese multinational corporation specializing in digital entertainment products. Pioneer wanted to help their customers check road and traffic conditions through in-car navigation systems. They developed a real-time, image-sharing service to help drivers navigate. The solution analyzes photos, diverts traffic, and sends alerts based on the observed conditions.  Because the pictures are of […]

Bewgle is an SAP.iO, Techstars-funded company that uses AWS services to surface insights from user-generated text and audio streams. Bewgle generates insights to help product managers to increase customer satisfaction and engagement with their various products—beauty, electronics, or anything in between.  By listening to the voices of their customers with the help of Bewgle powered […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. This is a guest post by Evan Harris, Manager of Machine Learning at Ibotta. In their own words, “Ibotta is transforming the shopping experience by making it easy for consumers to earn cash back on everyday purchases through a single […]

Are you a data scientist with data warehouse tables that you’d like to explore in your machine learning (ML) environment? If so, read on. In this post, I show you how to perform exploratory analysis on large datasets stored in your data warehouse and cataloged in your AWS Glue Data Catalog from your Amazon SageMaker […]

October 2021: Updating for airflow versions with MWAA supported releases, simplifying dependencies and adding Aurora Serverless as a DB option. In addition, new features (Session Manager integration and CloudFormation Stack status for the EC2 deployment) have been added. Machine learning (ML) workflows orchestrate and automate sequences of ML tasks by enabling data collection and transformation. […]

Good machine learning models are built with large volumes of high-quality training data. But creating this kind of training data is expensive, complicated, and time-consuming. To help a model learn how to make the right decisions, you typically need a human to manually label the training data. Amazon SageMaker Ground Truth provides labeling workflows for […]

Today, we introduce four new features of Amazon SageMaker Object2Vec: negative sampling, sparse gradient update, weight-sharing, and comparator operator customization. Amazon SageMaker Object2Vec is a general-purpose neural embedding algorithm. If you’re unfamiliar with Object2Vec, see the blog post Introduction to Amazon SageMaker Object2Vec, which provides a high-level overview of the algorithm with links to four notebook […]