aws-samples / deep-learning-models
Natural language processing & computer vision models optimized for AWS
☆141Updated 2 years ago
Alternatives and similar repositories for deep-learning-models:
Users that are interested in deep-learning-models are comparing it to the libraries listed below
- Distributed training with SageMaker's script mode using Horovod distributed deep learning framework☆32Updated 5 years ago
- Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.c…☆60Updated last month
- Toolkit for allowing inference and serving with MXNet in SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https…☆28Updated last year
- Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://gith…☆202Updated last month
- SageMaker specific extensions to TensorFlow.☆54Updated 7 months ago
- Amazon SageMaker Debugger provides functionality to save tensors during training of machine learning jobs and analyze those tensors☆161Updated 10 months ago
- A high performance data access library for machine learning tasks☆74Updated last year
- WARNING: This package has been deprecated. Please use the SageMaker Training Toolkit for model training and the SageMaker Inference Toolk…☆186Updated 4 years ago
- A TensorFlow Serving solution for use in SageMaker. This repo is now deprecated.☆172Updated last year
- Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https:…☆270Updated last month
- This is the documentation for AWS Deep Learning AMIs: your one-stop shop for deep learning in the cloud☆46Updated last year
- Neo-AI-DLR is a common runtime for machine learning models compiled by AWS SageMaker Neo, TVM, or TreeLite.☆494Updated last year
- Sample Jupyter Notebooks for Amazon Augmented AI (A2I)☆71Updated last year
- A recipe of SageMaker Ground Truth Lambdas to be used for creating labeling jobs with custom task type☆26Updated 2 years ago
- ☆145Updated 2 years ago
- Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.☆104Updated 2 years ago
- Dynamic training with Apache MXNet reduces cost and time for training deep neural networks by leveraging AWS cloud elasticity and scale. …☆56Updated 2 years ago
- Implementations of Amazon SageMaker-compatible custom containers for training.☆25Updated 4 years ago
- Amazon SageMaker MLOps deployment pipeline for A/B Testing of machine learning models.☆44Updated 3 years ago
- The open source version of the Amazon SageMaker docs☆251Updated last year
- CLI for building Docker images in SageMaker Studio using AWS CodeBuild.☆55Updated 2 years ago
- Some crazy experiments☆33Updated last month
- Over 60 example task UIs for Amazon Augmented AI (A2I)☆98Updated 4 years ago
- Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.☆98Updated 7 months ago
- Creates a CloudFormation template that uses AWS StepFunctions to automate the building and training of Sagemaker custom models based on S…☆165Updated 5 years ago
- Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many de…☆69Updated 9 months ago
- End to end code samples for training an object detection model in Amazon SageMaker using the built-in SSD algorithm and running it on AWS…☆39Updated 4 years ago
- Distributed Deep Learning on AWS Using CloudFormation (CFN), MXNet and TensorFlow☆254Updated 5 years ago
- ☆20Updated 2 years ago
- This workshop demonstrates two methods of machine learning inference for global production using AWS Lambda and Amazon SageMaker☆57Updated 4 years ago