Exam AI-102 topic 3 question 74 discussion

1. Create an Azure Machine Learning workspace. 2. Create and train the model in the Azure Machine Learning studio. 3. Create an endpoint for the model. 4. Connect the custom skill to the endpoint. 5. Rerun the indexer to enrich the index.

https://learn.microsoft.com/en-us/training/modules/build-azure-machine-learn-custom-skill-for-azure-cognitive-search/03-enrich-search-index-use-model 1.Create an Azure Machine Learning workspace. 2.Create and train the model in the Azure Machine Learning studio. 3.Create an endpoint for the model. 4.Provision an Azure AI Services resource and obtain the endpoint. 5.Connect the custom skill to the endpoint.

https://learn.microsoft.com/en-us/training/modules/create-azure-ai-custom-skill/5-ml-custom-skill 1. Create an Azure Machine Learning workspace. 2. Create and train the model in the Azure Machine Learning studio. 3. Create an endpoint for the model. 4. Connect the custom skill to the endpoint. 5. Rerun the indexer to enrich the index.

To implement an Azure AI Search resource that uses a custom skill based on sentiment analysis, follow these actions in sequence: Create an Azure Machine Learning workspace: Set up the environment where you can create and manage your machine learning experiments and models. Create and train the model in the Azure Machine Learning studio: Develop and train your custom sentiment analysis model using the resources in your Azure Machine Learning workspace. Create an endpoint for the model: Deploy your trained model and create an endpoint to access the model via REST API. Connect the custom skill to the endpoint: Configure Azure AI Search to use your custom skill by connecting it to the model's endpoint. Rerun the indexer to enrich the index: Update the search index by rerunning the indexer, which will now use the custom skill to analyze sentiment and enrich the data in the search index.

ChatGPT: 1- Provision an Azure AI Services resource and obtain the endpoint. 2- Create an Azure Machine Learning workspace. 3- Create and train the model in the Azure Machine Learning studio. 4- Create an endpoint for the model. 6- Connect the custom skill to the endpoint

1. Create an Azure Machine Learning workspace. 2. Create and train the model in the Azure Machine Learning studio. 3. Create an endpoint for the model. 4. Connect the custom skill to the endpoint. 5. Rerun the indexer to enrich the index.

Based on the detailed steps provided in the Microsoft Learn documentation, the sequence of actions indeed doesn't require provisioning a separate Azure AI Services resource. Instead, the custom skill is directly connected to the Azure Machine Learning model endpoint. https://learn.microsoft.com/en-us/training/modules/build-azure-machine-learn-custom-skill-for-azure-cognitive-search/03-enrich-search-index-use-model

1. Create an Azure Machine Learning workspace. 2. Create and train the model in the Azure Machine Learning studio. 3. Create an endpoint for the model. 4. Connect the custom skill to the endpoint. 5. Rerun the indexer to enrich the index.

Create an Azure Machine Learning workspace. Create and train the model in the Azure Machine Learning studio. Create an endpoint for the model. Provision an Azure AI Services resource and obtain the endpoint. Connect the custom skill the endpoint.

Create an Azure Machine Learning workspace. Create and train the model in the Azure Machine Learning studio. Create an endpoint for the model. Connect the custom skill to the endpoint. Rerun the indexer to enrich the index.

Create workspace Provision Connect Create studio Rerun

Create an Azure Machine Learning workspace. Create and train the model in the Azure Machine Learning studio. Create an endpoint for the model. Provision an Azure AI Services resource and obtain the endpoint. Connect the custom skill to the endpoint.

Create an endpoint for the model. Create and train the model in the Azure Machine Learning studio. Create an Azure Machine Learning workspace. Connect the custom skill to the endpoint. so, with the options: Create an Azure Machine Learning Create and train Provision an Azure Create an endpoint Connect

Create an Azure Machine Learning workspace. Create and train the model in the Azure Machine Learning studio. Create an endpoint for the model. Provision an Azure AI Services resource and obtain the endpoint. Connect the custom skill to the endpoint.

According to GPT4: 1. Create an Azure Machine Learning workspace. 2. Create and train the model in the Azure Machine Learning studio. 3. Provision an Azure AI Services resource and obtain the endpoint. 4. Create an endpoint for the model. Connect the custom skill to the endpoint. Rerun the indexer to enrich the index.