| awslabs/gluonts |
5,162 |
|
0 |
16 |
28 days ago |
107 |
December 07, 2023 |
385 |
apache-2.0 |
Python |
| Probabilistic time series modeling in Python |
| aws/sagemaker-python-sdk |
1,994 |
|
14 |
76 |
about 2 years ago |
554 |
November 30, 2023 |
272 |
apache-2.0 |
Python |
| A library for training and deploying machine learning models on Amazon SageMaker |
| aws/deep-learning-containers |
881 |
|
0 |
0 |
about 2 years ago |
0 |
|
126 |
other |
Python |
| AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. |
| awslabs/deeplearning-cfn |
244 |
|
0 |
0 |
about 6 years ago |
0 |
|
6 |
other |
Python |
| Distributed Deep Learning on AWS Using CloudFormation (CFN), MXNet and TensorFlow |
| awslabs/mxnet-lambda |
127 |
|
0 |
0 |
over 7 years ago |
0 |
|
7 |
apache-2.0 |
Python |
| Reference Lambda function that predicts image labels for a image using an MXNet-built deep learning model. The repo also has pre-built MXNet, OpenCV libraries for use with AWS Lambda. |
| aws-samples/machine-learning-using-k8s |
121 |
|
0 |
0 |
over 6 years ago |
0 |
|
7 |
apache-2.0 |
|
| Train and Deploy Machine Learning Models on Kubernetes using Amazon EKS |
| aws-samples/aws-ai-bootcamp-labs |
107 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
apache-2.0 |
Jupyter Notebook |
| This library holds a collection of Notebooks and code examples for AWS AI Bootcamps. |
| sunilmallya/timeseries |
83 |
|
0 |
0 |
almost 8 years ago |
0 |
|
1 |
apache-2.0 |
Jupyter Notebook |
| Deep Learning repo for timeseries and sequence data |
| aws-samples/aws-panorama-samples |
79 |
|
0 |
0 |
over 2 years ago |
0 |
|
13 |
mit-0 |
Python |
| This repository has samples that demonstrate various aspects of AWS Panorama device and the Panorama SDK |
| aws/sagemaker-mxnet-training-toolkit |
60 |
|
0 |
0 |
over 5 years ago |
28 |
September 14, 2020 |
3 |
apache-2.0 |
Python |
| Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers. |
