AWS Machine Learning Blog

Proactively detecting unusual or unexpected variances in your business metrics and reducing false alarms can help you stay on top of sudden changes and improve your business performance. Accurately identifying the root cause of deviation from normal business metrics and taking immediate steps to remediate an anomaly can not only boost user engagement but also […]

Based in Dubai, Ounass is the Middle East’s leading ecommerce platform for luxury goods. Scouring the globe for leading trends, Ounass’s expert team reports on the latest fashion updates, coveted insider information, and exclusive interviews for customers to read and shop. With more than 230,000 unique catalog items spanning multiple brands and several product classes—including […]

Conversational interfaces have the potential to allow customers to interact more naturally with automated systems. From virtual assistants to concierge chatbots, conversational interfaces can bring convenience and personalization to customers at scale. However, these benefits depend not only on the technology that the Amazon Lex platform and other AWS services can provide, but also on […]

July 2023: This post was reviewed for accuracy. Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. It provides all the tools you need to take your models from experimentation to production while boosting your productivity. You can […]

In the era of Big Data, businesses are faced with a deluge of time series data. This data is not just available in high volumes, but is also highly nuanced. Amazon Forecast Deep Learning algorithms such as DeepAR+ and CNN-QR build representations that effectively capture common trends and patterns across these numerous time series. These […]

This is a guest post by Shae Selix (Staff Data Scientist at Calm) and Luis Lopez Soria (Sr. AI/ML Specialist SA at AWS). Today, content is proliferating. It’s being produced in many different forms by a host of content providers, both large and small. Whether it’s on-demand video, music, podcasts, or other forms of rich […]

When we analyze images, we may want to incorporate other metadata related to the image. Examples include when and where the image was taken, who took the image, as well as what is featured in the image. One way to represent this metadata is to use a JSON format, which is well-suited for a document […]

Modern quantitative finance is based around the approach of pattern recognition in historical data. This approach requires teams of scientists to work in a collaborative and regulated setting in order to develop models that can be used to make trading predictions. With the growing influence of this field, both participants and regulators are looking to […]

Amazon Rekognition Custom Labels allows you to extend the object and scene detection capabilities of Amazon Rekognition to extract information from images that is uniquely helpful to your business. For example, you can find your logo in social media posts, identify your products on store shelves, classify machine parts in an assembly line, distinguish healthy […]

In this post, we discuss how to use the AWS Cloud and its services to accelerate observational studies for life sciences customers. We provide a reference architecture for architects, business owners, and technology decision-makers in the life sciences industry to automate the processes in clinical studies. Observational studies lead the way in research, allowing you […]