AWS Machine Learning Blog

Tag: sagemaker

Amazon SageMaker JumpStart landing page

Zero-shot text classification with Amazon SageMaker JumpStart

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. Recently, state-of-the-art architectures like the transformer architecture are used to achieve near-human performance on NLP downstream tasks like text summarization, text classification, entity recognition, […]

Build a machine learning model to predict student performance using Amazon SageMaker Canvas

There has been a paradigm change in the mindshare of education customers who are now willing to explore new technologies and analytics. Universities and other higher learning institutions have collected massive amounts of data over the years, and now they are exploring options to use that data for deeper insights and better educational outcomes. You […]

Best practices for TensorFlow 1.x acceleration training on Amazon SageMaker

Today, a lot of customers are using TensorFlow to train deep learning models for their clickthrough rate in advertising and personalization recommendations in ecommerce. As the behavior of their clients change, they can accumulate large amounts of new data every day. Model iteration is one of a data scientist’s daily jobs, but they face the […]

Feature Group Update workflow

Simplify iterative machine learning model development by adding features to existing feature groups in Amazon SageMaker Feature Store

Feature engineering is one of the most challenging aspects of the machine learning (ML) lifecycle and a phase where the most amount of time is spent—data scientists and ML engineers spend 60–70% of their time on feature engineering. AWS introduced Amazon SageMaker Feature Store during AWS re:Invent 2020, which is a purpose-built, fully managed, centralized […]

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, […]