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Firstly, you should know that After i say parameters I mean our vector of theta that's a second vector that contains the intercept and slope of our speculation line.

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In this element, we are carrying out some thing termed element normalization. That is a trick which is Utilized in equipment Understanding lots and it turns out it genuinely helps gradient descent to succeed in convergence by normalizing the info, now Exactly what does that imply?

Rationalization: "The variance of the amount and nine" is the result of a subtraction of the two, so we write this as

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Farmers apply linear programming strategies for their operate. By deciding what crops they ought to develop, the quantity of it and the way to utilize it successfully, farmers can improve their income.

There's a chance you're thinking why I saved the min and max of x in variables prior to applying them, that is due to the fact down the road we're gonna have to normalize the input benefit so as to get the correct prediction.