machine learning

Model Representation:

m = no. of training examples

x’s = input variable / features

y’s = output variable / target variable

(x,y) – one training example

(xi,  yi) – ith training example

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Cost Function:

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Intuition 1:

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Algorithm: Gradient descent for minimizing J

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