AWS News Blog

Category: Artificial Intelligence

AWS Machine Learning University New Educator Enablement Program to Build Diverse Talent for ML/AI Jobs

AWS Machine Learning University is now providing a free educator enablement program. This program provides faculty at community colleges, minority-serving institutions (MSIs), and historically Black colleges and universities (HBCUs) with the skills and resources to teach data analytics, artificial intelligence (AI), and machine learning (ML) concepts to build a diverse pipeline for in-demand jobs of […]

New — Introducing Support for Real-Time and Batch Inference in Amazon SageMaker Data Wrangler

To build machine learning models, machine learning engineers need to develop a data transformation pipeline to prepare the data. The process of designing this pipeline is time-consuming and requires a cross-team collaboration between machine learning engineers, data engineers, and data scientists to implement the data preparation pipeline into a production environment. The main objective of […]

New — Amazon SageMaker Data Wrangler Supports SaaS Applications as Data Sources

Data fuels machine learning. In machine learning, data preparation is the process of transforming raw data into a format that is suitable for further processing and analysis. The common process for data preparation starts with collecting data, then cleaning it, labeling it, and finally validating and visualizing it. Getting the data right with high quality […]

ML Governance Tools for Amazon SageMaker

New ML Governance Tools for Amazon SageMaker – Simplify Access Control and Enhance Transparency Over Your ML Projects

As companies increasingly adopt machine learning (ML) for their business applications, they are looking for ways to improve governance of their ML projects with simplified access control and enhanced visibility across the ML lifecycle. A common challenge in that effort is managing the right set of user permissions across different groups and ML activities. For […]

Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data

You use map apps every day to find your favorite restaurant or travel the fastest route using geospatial data. There are two types of geospatial data: vector data that uses two-dimensional geometries such as a building location (points), roads (lines), or land boundary (polygons), and raster data such as satellite and aerial images. Last year, […]

Amazon SageMaker Studio

New – Redesigned UI for Amazon SageMaker Studio

Today, I’m excited to announce a new, redesigned user interface (UI) for Amazon SageMaker Studio. SageMaker Studio provides a single, web-based visual interface where you can perform all machine learning (ML) development steps with a comprehensive set of ML tools. For example, you can prepare data using SageMaker Data Wrangler, build ML models with fully […]

Introducing Amazon Omics – A Purpose-Built Service to Store, Query, and Analyze Genomic and Biological Data at Scale

You might learn in high school biology class that the human genome is composed of over three billion letters of code using adenine (A), guanine (G), cytosine (C), and thymine (T) paired in the deoxyribonucleic acid (DNA). The human genome acts as the biological blueprint of every human cell. And that’s only the foundation for […]

Classifying and Extracting Mortgage Loan Data with Amazon Textract

Mortgage loan applications, at least in the United States, comprise around 500 or more pages of diverse documents. In order for applications to be reviewed, all these documents need to be classified, and the data on each form extracted. This isn’t as easy as it might sound! Besides different data structures in each document, the […]