AWS Machine Learning Blog

AUGUST 22, 2023

When choosing an FL framework, we usually consider its support for model category, ML framework, and device or operation system. The Flower clients receive instructions (messages) as raw byte arrays via the network. Instances in either VPC can communicate with each other as if they are within the same network.

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The MLOps Blog

OCTOBER 3, 2023

But more importantly, they’re not actually doing the important thing that you do with social networks, which is you have to actually engage with people. It’s almost like a very specialized data storage solution. It kind of replaces your storage, right? You have to share with folks. You have to produce your learnings.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

Afterwards, model artifacts are produced and stored in an output Amazon Simple Storage Service (Amazon S3) bucket, and a new model version is logged in the SageMaker model registry. Without modifying the existing architecture , we decide to fine-tune three separate pre-trained models for each of our required categories.

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AWS Machine Learning Blog

JULY 13, 2023

Recent years have shown amazing growth in deep learning neural networks (DNNs). Amazon SageMaker distributed training jobs enable you with one click (or one API call) to set up a distributed compute cluster, train a model, save the result to Amazon Simple Storage Service (Amazon S3), and shut down the cluster when complete.

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The MLOps Blog

DECEMBER 29, 2022

Again, to attach stack to it, I’ve worked… I’m in the ML hosting space, and I’ve worked with dozens of people, and 90% of people aren’t utilizing the GPU- more than half, and they don’t realize it. Don’t attach it to an outcome, just force yourself to get in the weeds a little.

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AWS Machine Learning Blog

JANUARY 9, 2023

This includes loading the model from Amazon Simple Storage Service (Amazon S3), for example, database lookups to validate the input, obtaining pre-computed features from the feature store, and so on. The infrastructure costs are the combined costs for storage, network, and compute. Throughput (transactions per second).

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