AWS Machine Learning

AutoGluon-Tabular is an open-source AutoML framework that requires only a single line of Python to train highly accurate machine learning (ML) models on an unprocessed tabular dataset. In this post, we walk you […]

Domestic infrastructure issues are a pain for everyone involved. Not only does it negatively affect customer satisfaction, it also has a cascading effect on businesses and their bottom line in terms of financials. […]

After the article in Nature about the open-source of AlphaFold v2.0 on GitHub by DeepMind, many in the scientific and research community have wanted to try out DeepMind’s AlphaFold implementation firsthand. With c […]

Out-of-stock (OOS) is an essential metric tracked across the retail industry. Brick-and-mortar retailers seek to reduce their costs associated with OOS items, while simultaneously increasing shopper satisfaction […]

This blog post was co-authored, and includes an introduction, by Aaron Brunko, Senior Vice President, Claims Product at Xactware.
Property insurance claims involving the valuation and replacement of personal […]

Today, we’re excited to announce RStudio on Amazon SageMaker, the industry’s first fully-managed RStudio integrated development environment (IDE) in the cloud. You can now bring the current RStudio licenses and […]

Today, we announced RStudio on Amazon SageMaker, the first machine learning (ML) integrated development environment (IDE) in the cloud for data scientists working in R. The open-source language R and its rich […]

Training your machine learning (ML) model and serving predictions is usually not the end of the ML project. The accuracy of ML models can deteriorate over time, a phenomenon known as model drift. Many factors can […]

If you have a corpus of internal documents that you frequently search through, Amazon Kendra can help you find your content faster and easier. These documents can be in different locations and repositories, and […]

Many organizations spanning different sizes and industry verticals still rely on large volumes of documents to run their day-to-day operations. To solve this business challenge, customers are using intelligent […]

Auto insurance companies are focusing on digital innovations to meet customer needs. Digital-first engagements provide tailored coverage, transparent information, and seamless experiences. The shift to virtual […]

As air travel starts to pick up in many parts of the world, digitization continues to transform the aviation industry. Airlines are working to reduce the number of touchpoints at the airport. Best practices have […]

Implementing an effective fraud prevention system is one of the top priorities for businesses that operate online web or mobile platforms. Businesses report millions of dollars of lost revenue each year due to […]

Retailers want to stay engaged with their customers as they move seamlessly between digital channels and physical storefronts. By delivering personalized and consistent experiences across a range of retail […]

Mobile service providers manage a high volume of customer service calls daily. Rapidly evolving network technology and device innovations are shaping customer expectations. Delighting callers with a quick […]

This is a guest post written by Gergely Kadi, Senior Systems Engineer and Martin Petraschek-Stummer, Senior Data Engineer at TourRadar.
TourRadar is a travel marketplace to connect people to life-enriching travel […]

SageMaker Projects give organizations the ability to easily setup and standardize developer environments for data scientists and CI/CD systems for MLOps Engineers. With SageMaker Projects, MLOps engineers or […]

Amazon Polly is a service that turns text into natural-sounding speech, using dozens of voices in more than 30 languages. You can use it for all sorts of applications, ranging from talking animated avatars, to […]

Amazon SageMaker is a fully managed service that provides every machine learning (ML) developer and data scientist the ability to build, train, and deploy ML models at scale. Amazon SageMaker Studio is a […]

One of the main challenges in a machine learning (ML) project implementation is the variety and high number of development artifacts and tools used. This includes code in notebooks, modules for data processing and […]