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amazon-sagemaker-examples icon amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

awsome-distributed-training icon awsome-distributed-training

Collection of best practices, reference architectures, model training examples and utilities to train large models on AWS.

deep-learning-containers icon deep-learning-containers

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

dynamic-training-with-apache-mxnet-on-aws icon dynamic-training-with-apache-mxnet-on-aws

Dynamic training with Apache MXNet reduces cost and time for training deep neural networks by leveraging AWS cloud elasticity and scale. The system reduces training cost and time by dynamically updating the training cluster size during training, with minimal impact on model training accuracy.

incubator-mxnet icon incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

incubator-mxnet-ci icon incubator-mxnet-ci

Continuous Integration and other infrastructure code that serves Apache MXNet incubating. This repository is not intended for end-users.

mxnet-on-lambda icon mxnet-on-lambda

This repo contains the example files for <MXNet on Lambda> blog post

sagemaker-mxnet-inference-toolkit icon sagemaker-mxnet-inference-toolkit

Toolkit for allowing inference and serving with MXNet in SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.

sagemaker-pytorch-inference-toolkit icon sagemaker-pytorch-inference-toolkit

Toolkit for allowing inference and serving with PyTorch on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.

web-data icon web-data

The repo to host all the web data including images for documents in dmlc projects.

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