AWS Machine Learning Blog

Category: Case Study

Bundesliga Match Fact Skill: Quantifying football player qualities using machine learning on AWS

In football, as in many sports, discussions about individual players have always been part of the fun. “Who is the best scorer?” or “Who is the king of defenders?” are questions perennially debated by fans, and social media amplifies this debate. Just consider that Erling Haaland, Robert Lewandowski, and Thomas Müller alone have a combined […]

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How Kustomer utilizes custom Docker images & Amazon SageMaker to build a text classification pipeline

This is a guest post by Kustomer’s Senior Software & Machine Learning Engineer, Ian Lantzy, and AWS team Umesh Kalaspurkar, Prasad Shetty, and Jonathan Greifenberger. In Kustomer’s own words, “Kustomer is the omnichannel SaaS CRM platform reimagining enterprise customer service to deliver standout experiences. Built with intelligent automation, we scale to meet the needs of […]

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How InpharmD uses Amazon Kendra and Amazon Lex to drive evidence-based patient care

The intersection of DI and AI: Drug information refers to the discovery, use, and management of healthcare and medical information. Healthcare providers have many challenges associated with drug information discovery, such as intensive time involvement, lack of accessibility, and accuracy of reliable data. The average clinical query requires a literature search that takes an average of 18.5 hours. In addition, drug information often lies in disparate information silos, behind pay walls and design walls, and quickly becomes stale.

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How SIGNAL IDUNA operationalizes machine learning projects on AWS

This post is co-authored with Jan Paul Assendorp, Thomas Lietzow, Christopher Masch, Alexander Meinert, Dr. Lars Palzer, Jan Schillemans of SIGNAL IDUNA. At SIGNAL IDUNA, a large German insurer, we are currently reinventing ourselves with our transformation program VISION2023 to become even more customer oriented. Two aspects are central to this transformation: the reorganization of […]

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How Süddeutsche Zeitung optimized their audio narration process with Amazon Polly

This is a guest post by Jakob Kohl, a Software Developer at the Süddeutsche Zeitung. Süddeutsche Zeitung is one of the leading quality dailies in Germany when it comes to paid subscriptions and unique users. Its website, SZ.de, reaches more than 15 million monthly unique users as of October 2021. Thanks to smart speakers and […]

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How Clearly accurately predicts fraudulent orders using Amazon Fraud Detector

This post was cowritten by Ziv Pollak, Machine Learning Team Lead, and Sarvi Loloei, Machine Learning Engineer at Clearly. The content and opinions in this post are those of the third-party authors and AWS is not responsible for the content or accuracy of this post. A pioneer in online shopping, Clearly launched their first site […]

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How Logz.io accelerates ML recommendations and anomaly detection solutions with Amazon SageMaker

Logz.io is an AWS Partner Network (APN) Advanced Technology Partner with AWS Competencies in DevOps, Security, and Data & Analytics. Logz.io offers a software as a service (SaaS) observability platform based on best-in-class open-source software solutions for log, metric, and tracing analytics. Customers are sending an increasing amount of data to Logz.io from various data […]

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Label text for aspect-based sentiment analysis using SageMaker Ground Truth

The Amazon Machine Learning Solutions Lab (MLSL) recently created a tool for annotating text with named-entity recognition (NER) and relationship labels using Amazon SageMaker Ground Truth. Annotators use this tool to label text with named entities and link their relationships, thereby building a dataset for training state-of-the-art natural language processing (NLP) machine learning (ML) models. Most […]

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Industrial automation at Tyson with computer vision, AWS Panorama, and Amazon SageMaker

This is the first in a two-part blog series on how Tyson Foods, Inc., is utilizing machine learning to automate industrial processes at their meat packing plants by bringing the benefits of artificial intelligence applications at the edge. In part one, we discuss an inventory counting application for packaging lines built using Amazon SageMaker and […]

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Develop an automatic review image inspection service with Amazon SageMaker

This is a guest post by Jihye Park, a Data Scientist at MUSINSA.  MUSINSA is one of the largest online fashion platforms in South Korea, serving 8.4M customers and selling 6,000 fashion brands. Our monthly user traffic reaches 4M, and over 90% of our demographics consist of teens and young adults who are sensitive to […]

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