MLOps workflow with Github Actions
Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry....
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| Format: | eBook |
| Language: | English |
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[Erscheinungsort nicht ermittelbar], Boston, MA
Pragmatic AI Solutions, Safari
2021
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| Edition: | 1st edition |
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| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the https://github.com/alfredodeza/flask-roberta repository Topics include: * Create a container that does live inferencing with Flask and the ONNX runtime * Package the model and verify it works locally * Setup a Github Action to authenticate to Azure ML and download a previously registered model * Build the new container as a Github Action, authenticate to Docker Hub or Github Packages * Push the new container to the Github registry or any other registry like Docker Hub |
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| Item Description: | Online resource; Title from title screen (viewed March 5, 2021) |
| Physical Description: | 1 video file, circa 1 hr., 6 min. |