Favorite 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
Favorite 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
Favorite 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
Favorite Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. This post shows how you can mask profane words and phrases with a grawlix string (“?$#@$”). Amazon Translate typically chooses clean words for your translation output. But in some situations, you want
Favorite Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. Often, customers have objects in S3 buckets that need further processing to be used effectively by consuming applications. Data engineers must support these application-specific data views with trade-offs between
Favorite Intelligent document processing (IDP) is a common use case for customers on AWS. You can utilize Amazon Comprehend and Amazon Textract for a variety of use cases ranging from document extraction, data classification, and entity extraction. One specific industry that uses IDP is insurance. They use IDP to automate data extraction for common
Favorite The AWS Machine Learning Operations (MLOps) framework is an iterative and repetitive process for evolving AI models over time. Like DevOps, practitioners gain efficiencies promoting their artifacts through various environments (such as quality assurance, integration, and production) for quality control. In parallel, customers rapidly adopt multi-account strategies through AWS
Favorite As humans, we constantly learn from the world around us. We experience inputs that shape our knowledge — including the boundaries of both what we know and what we don’t know. Many of today’s machines also learn by example. However, these machines are typically trained on datasets and information
Favorite Many of our AWS customers provide research, analytics, and business intelligence as a service. This type of research and business intelligence enables their end customers to stay ahead of markets and competitors, identify growth opportunities, and address issues proactively. For example, some of our financial services sector customers do
Favorite It is generally acknowledged that KM requires a culture of trust. But is remote working eroding trust, and what might this do to KM? Trust by Vic on Flickr There are many studies of the links between Knowledge Management and trust (see here, here, and here for example). Without
Shared by AWS Machine Learning February 16, 2022
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