Master Gradient Descent and Error Correction in Machine Learning

Gradient Descent is an optimization algorithm used to minimize the error function in machine learning models. It works by iteratively adjusting the model's parameters in the direction of steepest descent. Error correction refers to the process of updating the model's parameters based on the calculated error between the predicted output and the actual output during training.

A way to calculate the error of a machine learning model

A method used to minimize the error of a machine learning model by adjusting its parameters (correct)

A process of randomly selecting data points to train a machine learning model

A technique used to maximize the accuracy of a machine learning model by adjusting its parameters

To maximize the accuracy of a machine learning model

To calculate the error of a machine learning model

To randomly select data points for training

To minimize the error of a machine learning model (correct)

<p>By adjusting the parameters of the model based on the error gradient</p> Signup and view all the answers