AWS Machine Learning Blog

SEPTEMBER 18, 2024

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Further optimization is possible using SageMaker Training Compiler to compile deep learning models for training on supported GPU instances. SageMaker Training Compiler converts deep learning models from high-level language representation to hardware-optimized instructions.

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AWS Machine Learning Blog

APRIL 27, 2023

Deep learning (DL) is a fast-evolving field, and practitioners are constantly innovating DL models and inventing ways to speed them up. Custom operators are one of the mechanisms developers use to push the boundaries of DL innovation by extending the functionality of existing machine learning (ML) frameworks such as PyTorch.

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AWS Machine Learning Blog

JUNE 13, 2023

This post is co-written with Jad Chamoun, Director of Engineering at Forethought Technologies, Inc. and Salina Wu, Senior ML Engineer at Forethought Technologies, Inc. In addition, deployments are now as simple as calling Boto3 SageMaker APIs and attaching the proper auto scaling policies. 2xlarge instances.

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The MLOps Blog

JUNE 27, 2023

Can you see the complete model lineage with data/models/experiments used downstream? Some of its features include a data labeling workforce, annotation workflows, active learning and auto-labeling, scalability and infrastructure, and so on. MLOps workflows for computer vision and ML teams Use-case-centric annotations.

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Heartbeat

SEPTEMBER 6, 2023

There are machine learning platforms that can perform all these tasks, and Comet is one such platform. Comet Comet is a machine learning platform built to help data scientists and ML engineers track, compare, and optimize machine learning experiments. We will build our deep learning model using those parameters.

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AWS Machine Learning Blog

MARCH 1, 2023

The ETL pipeline, MLOps pipeline, and ML inference should be rebuilt in a different AWS account. To solve this problem, we make the ML solution auto-deployable with a few configuration changes. ML engineers no longer need to manage this training metadata separately. We define another pipeline step, step_cond.

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