Artificial Intelligence

Category: Amazon Machine Learning

Build XGBoost models with Amazon Redshift ML

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how customers can use the automatic model training capability of Amazon Redshift to train their classification and regression models. Redshift ML provides several capabilities for data scientists. It allows you to create […]

Automate Amazon SageMaker Studio setup using AWS CDK

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, move […]

Build patient outcome prediction applications using Amazon HealthLake and Amazon SageMaker

Healthcare data can be challenging to work with and AWS customers have been looking for solutions to solve certain business challenges with the help of data and machine learning (ML) techniques. Some of the data is structured, such as birthday, gender, and marital status, but most of the data is unstructured, such as diagnosis codes […]

Build multi-class classification models with Amazon Redshift ML

July 2024: This post was reviewed and updated for accuracy. Amazon Redshift ML simplifies the use of machine learning (ML) by using simple SQL statements to create and train ML models from data in Amazon Redshift. You can use Amazon Redshift ML to solve binary classification, multi-class classification, and regression problems and can use either AutoML or […]

Build regression models with Amazon Redshift ML

June 2023: This post was reviewed and updated for accuracy. With the rapid growth of data, many organizations are finding it difficult to analyze their large datasets to gain insights. As businesses rely more and more on automation algorithms, machine learning (ML) has become a necessity to stay ahead of the competition. Amazon Redshift, a […]

DeepLearning.AI, Coursera, and AWS launch the new Practical Data Science Specialization with Amazon SageMaker

Amazon Web Services (AWS), Coursera, and DeepLearning.AI are excited to announce Practical Data Science, a three-course, 10-week, hands-on specialization designed for data professionals to quickly learn the essentials of machine learning (ML) in the AWS Cloud. DeepLearning.AI was founded in 2017 by Andrew Ng, an ML and education pioneer, to fill a need for world-class […]

Gain valuable ML skills with the AWS Machine Learning Engineer Nanodegree Scholarship from Udacity

Support for AWS DeepComposer will be ending soon. Please see Support for AWS DeepComposer ending soon for more details. Amazon Web Services is partnering with Udacity to help educate developers of all skill levels on machine learning (ML) concepts with the AWS Machine Learning Scholarship Program by Udacity by offering 425 scholarships, with a focus […]

Build a cognitive search and a health knowledge graph using AWS AI services

Medical data is highly contextual and heavily multi-modal, in which each data silo is treated separately. To bridge different data, a knowledge graph-based approach integrates data across domains and helps represent the complex representation of scientific knowledge more naturally. For example, three components of major electronic health records (EHR) are diagnosis codes, primary notes, and […]

AWS launches free digital training courses to empower business leaders with ML knowledge

Today, we’re pleased to launch Machine Learning Essentials for Business and Technical Decision Makers—a series of three free, on-demand, digital-training courses from AWS Training and Certification. These courses are intended to empower business leaders and technical decision makers with the foundational knowledge needed to begin shaping a machine learning (ML) strategy for their organization, even […]