AWS Machine Learning Blog

Category: Artificial Intelligence

Automate weed detection in farm crops using Amazon Rekognition Custom Labels

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 […]

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Fine-tune and deploy the ProtBERT model for protein classification using Amazon SageMaker

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 […]

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

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 […]

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How Contentsquare reduced TensorFlow inference latency with TensorFlow Serving on Amazon SageMaker

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 […]

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Host multiple TensorFlow computer vision models using Amazon SageMaker multi-model endpoints

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, […]

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Your Guide to the AWS Machine Learning Summit

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 […]

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It’s a wrap for Amazon SageMaker Month, 30 days of content, discussions, and news

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, […]

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Enhance sports narratives with natural language generation using Amazon SageMaker

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 […]

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How lekker got more insights into their customer churn model with Amazon SageMaker Debugger

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 […]

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Best practices in customer service automation

Chatbots, virtual assistants, and Interactive Voice Response (IVR) systems are key components of successful customer service strategies. We had the pleasure of hearing from three AWS Contact Center Intelligence (AWS CCI) Partners as part of our Best Practices in Customer Service Automation webinar, who provided valuable insights and tips for building automated, customer-service solutions. The […]

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