AWS Machine Learning Blog

July 2023: This post was reviewed for accuracy. Please refer to Deploying ML models using SageMaker Serverless Inference, a new inference option that enables you to easily deploy machine learning models for inference without having to configure or manage the underlying infrastructure. In AWS, you can host a trained model multiple ways, such as via […]

Amazon Rekognition Custom Labels makes automated weed detection in crops easier. Instead of manually locating weeds, you can automate the process with Amazon Rekognition Custom Labels, which allows you to build machine learning (ML) models that can be trained with only a handful of images and yet are capable of accurately predicting which areas of […]

Proteins, the key fundamental macromolecules governing in biological bodies, are composed of amino acids. These 20 essential amino acids, each represented by a capital letter, combine to form a protein sequence, which can be used to predict the subcellular localization (the location of protein in a cell) and structure of proteins. Figure 1: Protein Sequence […]

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 on women and underrepresented groups. Machine learning is an exciting and rapidly developing technology that has the power to […]

In this post, we present the results of a model serving experiment made by Contentsquare scientists with an innovative DL model trained to analyze HTML documents. We show how the Amazon SageMaker TensorFlow Serving solution helped Contentsquare address several serving challenges. Contentsquare’s challenge Contentsquare is a fast-growing French technology company empowering brands to build better […]

Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. SageMaker accelerates innovation within your organization by providing purpose-built tools for every step of ML development, including labeling, data preparation, feature engineering, statistical bias detection, AutoML, […]

We’re about a week away from the AWS Machine Learning Summit and if you haven’t registered yet, you better get on it! On June 2, 2021 (Americas) and June 3, 2021 (Asia-Pacific, Japan, Europe, Middle East, and Africa), don’t miss the opportunity to hear from some of the brightest minds in machine learning (ML) at […]

Did you miss SageMaker Month? Don’t look any further than this round-up post to get caught up. In this post, we share key highlights and learning materials to accelerate your machine learning (ML) innovation. On April 20, 2021, we launched the first ever Amazon SageMaker Month, 30 days of hands-on workshops, tech talks, Twitch sessions, […]

This blog post was co-authored by Arbi Tamrazian, Director of Data Science and Machine Learning at Fox Sports. FOX Sports is the sports television arm of FOX Network. The company used machine learning (ML) and Amazon SageMaker to streamline the production of relevant in-game storylines for commentators to use during live broadcasts. “We collaborated with […]

With over 400,000 customers, lekker Energie GmbH is a leading supraregional provider of electricity and gas on the German energy market. lekker is customer and service oriented and regularly scores top marks in comparison tests. As one of the most important suppliers of green electricity to private households, the company, with its 220 employees, stands […]