Category: Application Services

July 2022: Post was reviewed for accuracy. Amazon SageMaker enables organizations to build, train, and deploy machine learning models. Consumer-facing organizations can use it to enrich their customers’ experiences, for example, by making personalized product recommendations, or by automatically tailoring application behavior based on customers’ observed preferences. When building such applications, one key architectural consideration […]

As machine learning (ML) becomes a larger part of companies’ core business, there is a greater emphasis on reducing the time from model creation to deployment. In November of 2019, AWS released the AWS Step Functions Data Science SDK for Amazon SageMaker, an open-source SDK that allows developers to create Step Functions-based machine learning workflows […]

Amazon SageMaker is a complete machine learning (ML) workflow service for developing, training, and deploying models, lowering the cost of building solutions, and increasing the productivity of data science teams. Amazon SageMaker comes with many predefined algorithms. You can also create your own algorithms by supplying Docker images, a training image to train your model […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. As an avid podcast listener, I had always wished for an easy way to glimpse at the transcript of an episode to decide whether I should add it to my playlist (not all episode abstracts are equally helpful!). Another challenge […]

You can easily get started extracting meaningful metadata from your media files by using the Media Analysis Solution on AWS. The Media Analysis Solution provides AWS CloudFormation templates that you can use to start extracting meaningful metadata from your media files within minutes. With a web-based user interface, you can easily upload files and see the metadata that is automatically extracted. This solution uses Amazon Rekognition for facial recognition, Amazon Transcribe to create a transcript, and Amazon Comprehend to run sentiment analysis on the transcript. You can also upload your own images to an Amazon Rekognition collection and train the solution to recognize individuals. In this blog post, we’ll show you step-by step how to launch the solution and upload an image and video. You’ll be able to see firsthand how metadata is seamlessly extracted.