awslabs / dynamic-training-with-apache-mxnet-on-awsLinks
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.
☆56Updated 2 years ago
Alternatives and similar repositories for dynamic-training-with-apache-mxnet-on-aws
Users that are interested in dynamic-training-with-apache-mxnet-on-aws are comparing it to the libraries listed below
Sorting:
- ☆118Updated 2 years ago
- This is the documentation for AWS Deep Learning AMIs: your one-stop shop for deep learning in the cloud☆45Updated 2 years ago
- Natural language processing & computer vision models optimized for AWS☆142Updated 2 years ago
- Distributed Deep Learning on AWS Using CloudFormation (CFN), MXNet and TensorFlow☆252Updated 5 years ago
- Deep Learning Benchmarking Suite☆130Updated 2 years ago
- ONNX model format support for Apache MXNet☆96Updated 6 years ago
- Deep learning benchmark utility and optimization tips on EKS.☆48Updated 6 years ago
- Content consists of Jupyter Notebook tutorials walking through deep learning Frameworks (MXNet, Gluon) to Platforms (SageMaker, DeepLens)…☆28Updated 7 years ago
- MxNet to ONNX Exporter☆56Updated 7 years ago
- GraphPipe for python☆41Updated 7 years ago
- A Tutorial for Serving Tensorflow Models using Kubernetes☆88Updated last week
- Reference Lambda function that predicts image labels for a image using an MXNet-built deep learning model. The repo also has pre-built MX…☆133Updated 3 years ago
- [DEPRECATED] Amazon Deep Learning's Keras with Apache MXNet support☆289Updated 2 years ago
- A high performance data access library for machine learning tasks☆74Updated last year
- Scripts and instructions to facilitate running Deep Learning Tasks on Amazon EMR☆63Updated last year
- Deep Learning Dockerfiles☆157Updated 4 years ago
- Toolkit for allowing inference and serving with MXNet in SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https…☆28Updated 2 years ago
- Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.☆497Updated 2 years ago
- Train and Deploy Machine Learning Models on Kubernetes using Amazon EKS☆169Updated 6 years ago
- Serving PyTorch Models on AWS Lambda with Caffe2 & ONNX☆48Updated 8 years ago
- Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core☆172Updated 3 years ago
- Incubating project for xgboost operator☆77Updated 3 years ago
- ☆59Updated 3 years ago
- ML-Powered Developer Tools, using Kubeflow☆54Updated 3 years ago
- Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.c…☆60Updated 8 months ago
- Monitor your GPUs whether they are on a single computer or in a cluster☆162Updated 6 years ago
- A multi-user, distributed computing environment for running DL model training experiments on Intel® Xeon® Scalable processor-based system…☆392Updated last year
- [UNMAINTAINED] A starter pack for creating a lightweight responsive web app for Fast.AI PyTorch models.☆16Updated 6 years ago
- Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search☆110Updated 2 years ago
- An example project to deploy MXNet inference API with Docker on Amazon ECS. Uses CodePipeline and CodeBuild to build the image to deploy …☆49Updated 5 years ago