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:
- Natural language processing & computer vision models optimized for AWS☆142Updated 2 years ago
- ☆118Updated last year
- This is the documentation for AWS Deep Learning AMIs: your one-stop shop for deep learning in the cloud☆46Updated 2 years ago
- Open deep learning compiler stack for cpu, gpu and specialized accelerators☆90Updated last month
- Distributed Deep Learning on AWS Using CloudFormation (CFN), MXNet and TensorFlow☆252Updated 5 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
- 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 2 years ago
- Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.c…☆60Updated 7 months ago
- A Tutorial for Serving Tensorflow Models using Kubernetes☆87Updated 6 months ago
- Content consists of Jupyter Notebook tutorials walking through deep learning Frameworks (MXNet, Gluon) to Platforms (SageMaker, DeepLens)…☆28Updated 7 years ago
- A high performance data access library for machine learning tasks☆74Updated last year
- Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors☆162Updated last year
- Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.☆496Updated 2 years ago
- ONNX model format support for Apache MXNet☆96Updated 6 years ago
- ☆59Updated 3 years ago
- Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://gith…☆205Updated 2 weeks ago
- MxNet to ONNX Exporter☆56Updated 7 years ago
- Serving PyTorch Models on AWS Lambda with Caffe2 & ONNX☆48Updated 7 years ago
- [DEPRECATED] Amazon Deep Learning's Keras with Apache MXNet support☆289Updated 2 years ago
- Scripts and instructions to facilitate running Deep Learning Tasks on Amazon EMR☆63Updated last year
- Deep Learning Dockerfiles☆157Updated 4 years ago
- Train and Deploy Machine Learning Models on Kubernetes using Amazon EKS☆168Updated 6 years ago
- Deep Learning Benchmarking Suite☆130Updated 2 years ago
- [UNMAINTAINED] A starter pack for creating a lightweight responsive web app for Fast.AI PyTorch models.☆16Updated 6 years ago
- This tutorial walks you through how to implement a sentiment analysis model to classify movie reviews as either 'Positive' or 'Negative' …☆22Updated 6 years ago
- Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core☆174Updated 3 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
- GraphPipe for python☆41Updated 6 years ago
- [Deprecated] The TensorFlow Profiler (TFProf) UI provides a visual interface for profiling TensorFlow models.☆137Updated 6 years ago
- Amazon Bin Image Dataset Challenge☆54Updated 8 years ago