Which of the following stages are part of the generative AI model lifecycle mentioned in the course? (Select all that apply)1 pointManipulating the model to align with specific project needs.Deploying the model into the infrastructure and integrating it with the application.Performing regularizationDefining the problem and identifying relevant datasets.Selecting a candidate model and potentially pre-training a custom model.5.
Question
Which of the following stages are part of the generative AI model lifecycle mentioned in the course? (Select all that apply)1 pointManipulating the model to align with specific project needs.Deploying the model into the infrastructure and integrating it with the application.Performing regularizationDefining the problem and identifying relevant datasets.Selecting a candidate model and potentially pre-training a custom model.5.
Solution
All the stages mentioned are part of the generative AI model lifecycle:
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Defining the problem and identifying relevant datasets: This is the first step in any AI model lifecycle. It involves understanding the problem at hand and identifying the data that will be used to train the model.
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Selecting a candidate model and potentially pre-training a custom model: Once the problem and data are defined, the next step is to select a suitable model. This could be a pre-existing model or a custom model that is pre-trained on the identified data.
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Manipulating the model to align with specific project needs: After selecting the model, it is manipulated and fine-tuned to align with the specific needs of the project.
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Performing regularization: Regularization is a technique used to prevent overfitting of the model. It is an important step in the model lifecycle to ensure that the model generalizes well to unseen data.
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Deploying the model into the infrastructure and integrating it with the application: The final step is to deploy the trained model into the infrastructure where it can be integrated with the application and used to make predictions.
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