AWS Machine Learning Blog

Category: Compute

Visualizing TensorFlow training jobs with TensorBoard

TensorBoard is an open source toolkit for TensorFlow users that allows you to visualize a wide range of useful information about your model, from model graphs; to loss, accuracy, or custom metrics; to embedding projections, images, and histograms of weights and biases. This post demonstrates how to use TensorBoard with Amazon SageMaker training jobs, write […]

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How to run distributed training using Horovod and MXNet on AWS DL Containers and AWS  Deep Learning AMIs

Distributed training of large deep learning models has become an indispensable way of model training for computer vision (CV) and natural language processing (NLP) applications. Open source frameworks such as Horovod provide distributed training support to Apache MXNet, PyTorch, and TensorFlow. Converting your non-distributed Apache MXNet training script to use distributed training with Horovod only […]

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Amazon EC2 Inf1 instances featuring AWS Inferentia chips now available in five new Regions and with improved performance

Following strong customer demand, AWS has expanded the availability of Amazon EC2 Inf1 instances to five new Regions: US East (Ohio), Asia Pacific (Sydney, Tokyo), and Europe (Frankfurt, Ireland). Inf1 instances are powered by AWS Inferentia chips, which Amazon custom-designed to provide you with the lowest cost per inference in the cloud and lower barriers […]

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Facebook uses Amazon EC2 to evaluate the Deepfake Detection Challenge

In October 2019, AWS announced that it was working with Facebook, Microsoft, and the Partnership on AI on the first Deepfake Detection Challenge. Deepfake algorithms are the same as the underlying technology that has given us realistic animation effects in movies and video games. Unfortunately, those same algorithms have been used by bad actors to […]

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AWS to offer NVIDIA A100 Tensor Core GPU-based Amazon EC2 instances

Tens of thousands of customers rely on AWS for building machine learning (ML) applications. Customers like Airbnb and Pinterest use AWS to optimize their search recommendations, Lyft and Toyota Research Institute to develop their autonomous vehicle programs, and Capital One and Intuit to build and deploy AI-powered customer assistants. AWS offers the broadest and deepest […]

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Reducing player wait time and right sizing compute allocation using Amazon SageMaker RL and Amazon EKS

As a multiplayer game publisher, you may often need to either over-provision resources or manually manage compute allocation when launching or maintaining an online game to avoid long player wait times. You need to develop, configure, and deploy tools that help you monitor and control the compute allocation. This post demonstrates GameServer Autopilot, a new […]

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Building an interactive and scalable ML research environment using AWS ParallelCluster

When it comes to running distributed machine learning (ML) workloads, AWS offers you both managed and self-service offerings. Amazon SageMaker is a managed service that can help engineering, data science, and research teams save time and reduce operational overhead. AWS ParallelCluster is an open-source, self-service cluster management tool for customers who wish to maintain more […]

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Build, test, and deploy your Amazon Sagemaker inference models to AWS Lambda

Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. When you deploy an ML model, Amazon SageMaker leverages ML hosting instances to host the model and provides an API endpoint to provide inferences. It may also […]

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Optimizing TensorFlow model serving with Kubernetes and Amazon Elastic Inference

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 workloads on AWS. It allows you […]

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Turning unstructured text into insights with Bewgle powered by AWS

Bewgle is an SAP.iO, Techstars-funded company that uses AWS services to surface insights from user-generated text and audio streams. Bewgle generates insights to help product managers to increase customer satisfaction and engagement with their various products—beauty, electronics, or anything in between.  By listening to the voices of their customers with the help of Bewgle powered […]

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