Artificial Intelligence

Category: Amazon SageMaker

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 […]

Develop and deploy ML models using Amazon SageMaker Data Wrangler and Amazon SageMaker Autopilot

Data generates new value to businesses through insights and building predictive models. However, although data is plentiful, available data scientists are far and few. Despite our attempts in recent years to produce data scientists from academia and elsewhere, we still see a huge shortage that will continue into the near future. To accelerate model building, […]

Save costs by automatically shutting down idle resources within Amazon SageMaker Studio

July 2023: This post was reviewed for accuracy. The Github repository is maintained up to date. Amazon SageMaker Studio provides a unified, web-based visual interface where you can perform all machine learning (ML) development steps, making data science teams up to 10 times more productive. Studio gives you complete access, control, and visibility into each […]

Prepare data from Snowflake for machine learning with Amazon SageMaker Data Wrangler

Data preparation remains a major challenge in the machine learning (ML) space. Data scientists and engineers need to write queries and code to get data from source data stores, and then write the queries to transform this data, to create features to be used in model development and training. All of this data pipeline development […]

Unlock near 3x performance gains with XGBoost and Amazon SageMaker Neo

October 2021: This post has been updated with a new sample notebook for Amazon SageMaker Studio users.  When a model gets deployed to a production environment, inference speed matters. Models with fast inference speeds require less resources to run, which translates to cost savings, and applications that consume the models’ predictions benefit from the improved […]

Human-in-the-loop review of model explanations with Amazon SageMaker Clarify and Amazon A2I

Domain experts are increasingly using machine learning (ML) to make faster decisions that lead to better customer outcomes across industries including healthcare, financial services, and many more. ML can provide higher accuracy at lower cost, whereas expert oversight can ensure validation and continuous improvement of sensitive applications like disease diagnosis, credit risk management, and fraud […]

Annotate DICOM images and build an ML model using the MONAI framework on Amazon SageMaker

DICOM (Digital Imaging and Communications in Medicine) is an image format that contains visualizations of X-Rays and MRIs as well as any associated metadata. DICOM is the standard for medical professionals and healthcare researchers for visualizing and interpreting X-Rays and MRIs. The purpose of this post is to solve two problems: Visualize and label DICOM […]

Edelweiss improves cross-sell using machine learning on Amazon SageMaker

This post is co-written by Nikunj Agarwal, lead data scientist at Edelweiss Tokio Life Insurance. Edelweiss Tokio Life Insurance Company Ltd is a leading life insurance company in India. Its broad spectrum of offerings includes life insurance, health insurance, retirement policies, wealth enhancement schemes, education funding, and more. How are you being recommended a credit […]

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 […]