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How to Deploy Model in EAS

Last Updated: Jul 21, 2019

Elastic Algorithm Service (EAS) is seamlessly integrated with Machine Learning Studio and Data Science Workshop (DSW). This allows you to deploy models as RESTful APIs in multiple ways. For more information about online model service pricing, see Machine Learning Platform for AI pricing.

You can use the following methods to deploy models:

  1. Upload models to the console
  2. Use Machine Learning Studio
  3. Use DSW
  4. Use the EASCMD client

Upload models to the console

  • On the EAS-Online Model Service page, you can upload trained models and then deploy the models in a few steps.
  • If you are using a RAM user account, you must first use your Alibaba Cloud account to authorize the RAM user account. For more information about RAM user account authorization, see Authorize RAM user accounts
  • Click Upload and Deploy Models, and then follow the steps shown in the following figure to upload and deploy the model.consoleupload

Use Machine Learning Studio to deploy models

  • Machine Learning Studio is a console that allows you to drag and drop components to build models. To log on to Machine Learning Studio, click Machine Learning Studio. After you train a model in Machine Learning Studio, you can deploy the model to EAS.
  • The algorithms that support model deployment include GBDT binary classification, linear SVM, logistic regression for binary classification, logistic regression for multiclass classification, random forest, K-means, linear regression, GBDT regression, and TensorFlow. GBDT regression does not support inputting the Int type data. Before you deploy the model, make sure that the data input to the GBDT regression component is Double type.image.png

Use DSW to deploy models

DSW is an interactive deep learning development environment on the cloud. It provides high-performance GPU modules and an interactive programming environment. To log on to DSW, click DSW. DSW is built in with EASCMD, which allows you to deploy a model to EAS after you train the model in DSW.

  • Check your AccessKey ID and AccessKey Secret on the User Management page. If you are using a RAM user account, then you must use your Alibaba Cloud account to log on to the RAM console, select Users, and click the RAM user account to check the AccessKey information of the RAM user account.
  • To deploy a model in the DSW terminal, you only need to enter one command line. For more information about the model deployment command, see Use EASCMD

Use the EASCMD client to deploy models

  • The EASCMD client allows you to manage online model services on your server. You can create services, delete services, modify services, and view service status. You can download the EASCMD client from the following links:
  • To deploy a model, you must provide your AccessKey ID and AccessKey Secret for authentication. You can view your AccessKey information on the User Management page.
  • For more information, seeUse EASCMD