All Projects → Azure → Batchai

Azure / Batchai

Licence: mit
Repo for publishing code Samples and CLI samples for BatchAI service

Projects that are alternatives of or similar to Batchai

Dfn
Stars: ✭ 120 (-0.83%)
Mutual labels:  jupyter-notebook
Chatbot Retrieval
Dual LSTM Encoder for Dialog Response Generation
Stars: ✭ 1,547 (+1178.51%)
Mutual labels:  jupyter-notebook
Keywords2vec
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Depy
DePy 2015 Talk
Stars: ✭ 120 (-0.83%)
Mutual labels:  jupyter-notebook
Yolov3 Point
从零开始学习YOLOv3教程解读代码+注意力模块(SE,SPP,RFB etc)
Stars: ✭ 119 (-1.65%)
Mutual labels:  jupyter-notebook
Research public
Quantitative research and educational materials
Stars: ✭ 1,776 (+1367.77%)
Mutual labels:  jupyter-notebook
Tfeat
TFeat descriptor models for BMVC 2016 paper "Learning local feature descriptors with triplets and shallow convolutional neural networks"
Stars: ✭ 119 (-1.65%)
Mutual labels:  jupyter-notebook
Multilstm
keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS
Stars: ✭ 122 (+0.83%)
Mutual labels:  jupyter-notebook
Naturallanguagerecommendations
Getting recommendations from natural language
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Machine learning model
机器学习基本模型算法介绍(附加案例)
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Climatemodeling courseware
A collection of interactive lecture notes and assignments in Jupyter notebook format.
Stars: ✭ 119 (-1.65%)
Mutual labels:  jupyter-notebook
Limperg python
Repository with material for the Limperg Python course by Ties de Kok.
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Western constellations atlas of space
Code, data, and instructions to map every star you can see from Earth
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Mdm
A TensorFlow implementation of the Mnemonic Descent Method.
Stars: ✭ 120 (-0.83%)
Mutual labels:  jupyter-notebook
Deep learning explorations
Codes and experiments while learning and exploring deep learning for personal curiosity by doing online courses, personal projects and work.
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Pde Find
Stars: ✭ 119 (-1.65%)
Mutual labels:  jupyter-notebook
Pandas Videos
Jupyter notebook and datasets from the pandas Q&A video series
Stars: ✭ 1,716 (+1318.18%)
Mutual labels:  jupyter-notebook
Drl Portfolio Management
CSCI 599 deep learning and its applications final project
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook
Time Series Classification And Clustering With Reservoir Computing
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Stars: ✭ 120 (-0.83%)
Mutual labels:  jupyter-notebook
Pytorch Rl
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
Stars: ✭ 121 (+0%)
Mutual labels:  jupyter-notebook

Azure Batch AI

Note: Azure Batch AI is being retired. Support for this service will be retired incrementally. The capabilities of Azure Batch AI are now available as a managed compute target in Azure Machine Learning service. For more information, see What's happening to Batch AI?.

Welcome to our documenting page at https://docs.microsoft.com/azure/batch-ai

Updates

03.20.2018 You can find examples of using Java SDK with Batch AI at Azure Samples GitHub

03.20.2018 You can find examples of using C# SDK with Batch AI at Azure Samples GitHub

02.16.2018 Published Azure Batch AI environment variables

02.02.2018 Published a schema for job configuration file validation.

01.12.2018 Published NVIDIA DGX Container Registry usage instructions

11.15.2017 Java SDK is available

11.08.2017 Node.js SDK is available

10.11.2017 C# Nuget package Microsoft.Azure.Management.BatchAI is available on nuget.org.

10.09.2017 Azure BatchAI starts public preview on October 9th, 2017!

Batch AI Recipes

We have created recipes for popular AI frameworks to help you get started with Batch AI and submit jobs without being an expert on Azure compute, storage, and networking.

Microsoft Cognitive Toolkit

TensorFlow

Chainer/ChainerMN

Caffe

Caffe2

Horovod

PyTorch

Keras

We also host recipes for advanced topics including:

Batch-Scoring

Hyperparameter Tuning

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Help or Feedback


If you have any problems or questions, you can reach the Batch AI team at [email protected] or you can create an issue on GitHub.

We also welcome your contributions of additional sample notebooks, scripts, or other examples of working with Batch AI.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].