AI Engineering Degree Practice Exam 2025 - Free AI Engineering Practice Questions and Study Guide

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What is the first step in training a logistic regression model?

Use the cost function on the training set

Update weights with new parameter values

Calculate cost function gradient

Initialize the parameters

The first step in training a logistic regression model involves initializing the parameters. This is essential because the model needs a starting point to begin the optimization process. Parameters, such as weights associated with the input features, determine how the model makes predictions. In practice, parameters can be initialized to small random values or zeros, which sets the stage for the subsequent steps in training.

Once the parameters are initialized, the training process can advance through calculating the cost function, finding its gradient, and iteratively updating the parameters to minimize the cost. Each of these steps builds on the initialized parameters, making it a critical first action in the training process.

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