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Training a model refers to the process of teaching a machine learning algorithm to make predictions or decisions based on output data.
Training a model refers to the process of teaching a machine learning algorithm to make predictions or decisions based on output data.
False
Computational complexity in machine learning refers to the amount of computational resources, such as time and memory, required by an algorithm to perform a certain task as a function of the input size.
Computational complexity in machine learning refers to the amount of computational resources, such as time and memory, required by an algorithm to perform a certain task as a function of the input size.
True
Linear regression is a statistical method and a fundamental algorithm in machine learning used for modeling the relationship between a dependent variable (target) and one or more independent variables (features).
Linear regression is a statistical method and a fundamental algorithm in machine learning used for modeling the relationship between a dependent variable (target) and one or more independent variables (features).
True
Batch gradient descent and stochastic gradient descent are the same algorithm.
Batch gradient descent and stochastic gradient descent are the same algorithm.
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The equation for a linear relationship (a straight line) that represents the data can be expressed in the form of $y = mx + b$.
The equation for a linear relationship (a straight line) that represents the data can be expressed in the form of $y = mx + b$.
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