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Favorite This is the first in a two part series on Amazon Comprehend custom classification models. In Part 1 of this series, we look at how to build an AWS Step Functions workflow to automatically build, test, and deploy Amazon Comprehend custom classification models and endpoints. In Part 2, we
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Shared by AWS Machine Learning March 10, 2021
Favorite This is the second in a two part series on Amazon Comprehend custom classification models. In Part 1 of this series, we looked at how to build an AWS Step Functions workflow to automatically build, test, and deploy Amazon Comprehend custom classification models and endpoints. In Part 2, we
Read More Shared by AWS Machine Learning March 10, 2021
Favorite Have you ever thought about how artificial intelligence could be used to detect events during live sports broadcasts? With machine learning (ML) techniques, we introduce a scalable multimodal solution for event detection on sports video data. Recent developments in deep learning show that event detection algorithms are performing well
Read More Shared by AWS Machine Learning March 6, 2021
Favorite This blog post was co-authored by AWS and Max Kelsen. Max Kelsen is one of Australia’s leading Artificial Intelligence (AI) and Machine Learning (ML) solutions businesses. The company delivers innovation, directly linked to the generation of business value and competitive advantage to customers in Australia and globally, including Fortune
Read More Shared by AWS Machine Learning March 4, 2021
Favorite Amazon Web Services (AWS) offers a rich stack of artificial intelligence (AI) and machine learning (ML) services that help automate several components of the customer service industry. Amazon Polly, an AI generated text-to-speech service, enables you to automate and scale your interactive voice solutions, helping to improve productivity and
Read More Shared by AWS Machine Learning March 4, 2021
Favorite In 2019, AWS unveiled Amazon SageMaker Debugger, a SageMaker capability that enables you to automatically detect a variety of issues that may arise while a model is being trained. SageMaker Debugger captures model state data at specified intervals during a training job. With this data, SageMaker Debugger can detect
Read More Shared by AWS Machine Learning March 4, 2021
Favorite Open-source workflow managers are popular because they make it easy to orchestrate machine learning (ML) jobs for productions. Taking models into productions following a GitOps pattern is best managed by a container-friendly workflow manager, also known as MLOps. Kubeflow Pipelines (KFP) is one of the Kubernetes-based workflow managers used
Read More Shared by AWS Machine Learning March 3, 2021
Favorite You have Amazon Simple Storage Service (Amazon S3) buckets full of files containing incoming customer chats, product reviews, and social media feeds, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing happy thoughts or sad thoughts, translate their comments
Read More Shared by AWS Machine Learning February 27, 2021
Favorite In our Community Showcase, Amazon Web Services (AWS) highlights projects created by AWS Heroes and AWS Community Builders. We worked with AWS Machine Learning (ML) Heroes and AWS ML Community Builders to bring to life projects and use cases that detect custom objects with Amazon Rekognition Custom Labels. The
Read More Shared by AWS Machine Learning February 26, 2021
Favorite Data can be used in a variety of ways to satisfy the needs of different business units, such as marketing, sales, or product. In this post, we focus on using data to create personalized recommendations to improve end-user engagement. Most ecommerce applications consume a huge amount of customer data
Read More Shared by AWS Machine Learning February 26, 2021