Automated machine learning (automated ML or AutoML) in Azure Machine Learning is the specific capability designed to automate the iterative and time-consuming tasks of model development. It allows users to build, train, and deploy predictive models with high efficiency and productivity by automatically trying various algorithms and hyperparameter combinations. This process can be initiated through a user-friendly interface in the Azure Machine Learning studio, requiring minimal to no coding, which directly aligns with the requirement to "quickly build and deploy a predictive model without extensive coding."

A. ML pipelines are used to create and manage reproducible workflows for machine learning tasks, which typically requires coding and is focused on productionization and automation, not rapid initial model creation.

B. Copilot is a general term for an AI assistant that helps write code. While it can speed up coding, it does not eliminate the need for it in building a model.

C. DALL-E is a generative AI model within the Azure OpenAI Service used for creating images from text prompts, not for building predictive models from data.

1. Microsoft Learn

AI-900 Study Guide

"Describe automated machine learning": "Automated machine learning (often abbreviated to automated ML or AutoML) is a key capability in Azure Machine Learning that enables non-experts to create an effective machine learning model... It helps data scientists and developers save time by automating the iterative tasks..."

2. Microsoft Learn

"What is automated machine learning (AutoML)?": "Automated machine learning... is the process of automating the time-consuming

iterative tasks of machine learning model development. It allows data scientists

analysts

and developers to build ML models with high scale

efficiency

and productivity all while sustaining model quality."

3. Microsoft Learn

"What are Azure Machine Learning pipelines?": "An Azure Machine Learning pipeline is an independently executable workflow of a complete machine learning task... Pipelines are defined by using a Python SDK

or visually in Azure Machine Learning studio designer." This highlights that pipelines are for creating workflows

not the model itself in a no-code fashion.

4. Microsoft Learn

"What is Azure OpenAI Service?": Under the "Model summary" section

it lists "DALL-E models" as a "series of models that can generate original images from natural language." This confirms its purpose is image generation.