AWS Machine Learning Blog

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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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season-trend decomposition

Prepare time series data with Amazon SageMaker Data Wrangler

Time series data is widely present in our lives. Stock prices, house prices, weather information, and sales data captured over time are just a few examples. As businesses increasingly look for new ways to gain meaningful insights from time-series data, the ability to visualize data and apply desired transformations are fundamental steps. However, time-series data […]

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Automate a shared bikes and scooters classification model with Amazon SageMaker Autopilot

Amazon SageMaker Autopilot makes it possible for organizations to quickly build and deploy an end-to-end machine learning (ML) model and inference pipeline with just a few lines of code or even without any code at all with Amazon SageMaker Studio. Autopilot offloads the heavy lifting of configuring infrastructure and the time it takes to build […]

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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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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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How ReliaQuest uses Amazon SageMaker to accelerate its AI innovation by 35x 

Cybersecurity continues to be a top concern for enterprises. Yet the constantly evolving threat landscape that they face makes it harder than ever to be confident in their cybersecurity protections.

To address this, ReliaQuest built GreyMatter, an Open XDR-as-a-Service platform that brings together telemetry from any security and business solution, whether on-premises or in one or multiple clouds, to unify detection, investigation, response, and resilience.

In 2021, ReliaQuest turned to AWS to help it enhance its artificial intelligence (AI) capabilities and build new features faster.

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Hybrid ML

Introducing hybrid machine learning

Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude, and length of migrations may be […]

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