What is learning factor Assumptions for linear regressoon Model evaluation Bias variance trade off Gradient descent Auc Roc curve Python function writing (string based)

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Learning factor, assumptions for linear regression, model evaluation, bias-variance trade off, gradient descent, AUC-ROC curve, Python function writing.

Learning factor refers to the rate at which a model learns from the data, often used in gradient descent algorithms.
Assumptions for linear regression include linearity, independence, homoscedasticity, and normality of residuals.
Model evaluation involves metrics like mean squared error, R-squared, and cross-validation techniques.
Bias-variance trade off is the balance between underfitting and overfitting in a model.
Gradient descent is an optimization algorithm used to minimize the loss function in machine learning models.
AUC-ROC curve is a graphical representation of the performance of a classification model.
Python function writing involves creating functions using the Python programming language.

What is learning factor Assumptions for linear regressoon Model evaluation Bias variance trade off Gradient descent Auc Roc curve Python function writing (string based)

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