Favorite Amazon SageMaker supports all the popular deep learning frameworks, including TensorFlow. Over 85% of TensorFlow projects in the cloud run on AWS. Many of these projects already run in Amazon SageMaker. This is due to the many conveniences Amazon SageMaker provides for TensorFlow model hosting and training, including fully
Favorite This post offers a dive deep into how to use Amazon Elastic Inference with Amazon Elastic Kubernetes Service. When you combine Elastic Inference with EKS, you can run low-cost, scalable inference workloads with your preferred container orchestration system. Elastic Inference is an increasingly popular way to run low-cost inference
Favorite After you’ve trained and exported a TensorFlow model, you can use Amazon SageMaker to perform inferences using your model. You can either: Deploy your model to an endpoint to obtain real-time inferences from your model. Use batch transform to obtain inferences on an entire dataset stored in Amazon S3.
Favorite Launched at AWS re:Invent 2018, Amazon SageMaker Ground Truth helps you quickly build highly accurate training datasets for your machine learning models. Amazon SageMaker Ground Truth offers easy access to public and private human labelers, and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, Amazon
Favorite We’re excited to announce an end-to-end solution that leverages natural language processing to analyze and visualize unstructured text in your Amazon Elasticsearch Service domain with Amazon Comprehend in the AWS Cloud. You can deploy this solution in minutes with an AWS CloudFormation template and visualize your data in a
Favorite Amazon Comprehend is a natural language processing service that can extract key phrases, places, names, organizations, events, and even sentiment from unstructured text, and more. Customers usually want to add their own entity types unique to their business, like proprietary part codes or industry-specific terms. In November 2018, enhancements to
Favorite Amazon SageMaker is a modular, fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Training models is quick and easy using a set of built-in high-performance algorithms, pre-built deep learning frameworks, or using your own framework. To help
Favorite Amazon SageMaker provides a fully-managed service for data science and machine learning workflows. One of the most important capabilities of Amazon SageMaker is its ability to run fully-managed training jobs to train machine learning models. Visit the service console to train machine learning models yourself on Amazon SageMaker. Now you
Favorite This is a guest blog post by Jesse Brizzi, a computer vision research engineer at Curalate. At Curalate, we’re always coming up with new ways to use deep learning and computer vision to find and leverage user-generated content (UGC) and activate influencers. Some of these applications, like Intelligent Product
Favorite When Software Engineer Florian Thomas describes Deliveroo, he is talking about a rapidly growing, highly in-demand company. Everyone must eat, after all, and Deliveroo is, in his words, “on a mission to transform the way you order food.” Specifically, Deliveroo’s business is partnering with restaurants to bring customers their
Shared by AWS Machine Learning September 13, 2019
