Deploy deep learning workloads to production with Azure Machine Learning

Module
6 Units

Advanced

Data Scientist

Azure Machine Learning

Deploying large-scale models for real-time inferencing is challenging because of the model's size. Learn what you can do and which frameworks you can use to optimize your model's performance during model scoring.

Learning objectives

In this module, you'll learn:

To choose the appropriate inference strategy
To optimize model scoring with ONNX
To deploy Triton as a managed online endpoint

Prerequisites

Before starting this module, you should be familiar with the Azure Machine Learning service and training machine learning and deep learning models.

Introduction min
Choose the appropriate inference strategy min
Standardize model formats and scale model deployment with ONNX and Triton min
Exercise: Deploy an ONNX model with Triton in Azure Machine Learning min
Knowledge check min
Summary min