### Linear Regression

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__Linear Regression with one variable:-__

In the problem where we predict share prices(regression problems), we have seen few parameters that are responsible for the price change. A regression problem considering a single parameter is called as Linear Regression with one variable.Let's take export rate as our parameter and share price be our goal. A general plot be like,

We need a mathematical model to represent this trend. In this case, an equation of line touching maximum points.

Equation of line - y(o/p) = mx(i/p) + c

m = slope of line (responsible for the shape of line)

c = a constant that shifts the line vertically

In ML terms,

y becomes

**h(θ)**

m becomes

**θ₁**

c becomes

**θ၀**

So our model is

**h(θ) = xθ₁ + θ၀**

**h(θ) is also known as hypothesis function.**

For different values of

**θ₁**and

**θ၀**different lines will be obtained.

Our next task is to find the best model from these possibilities. Finding the best values for

**θ₁**and

**θ၀**is our goal. Learning Cost function will give us more idea about this.

On Next - Cost Function

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