Linear Regression

Linear Regression, Hypothesis and cost

guess Hypothesis and calculate the cost.

repeat change Hypothesis (W,b) the way cost is minimized.

actually, study hours (x) -> predict score(y) is one-variable linear regression

but in image processing, the image represents many pixels, matrix.(except image processing, there are many examples using multi-variable)

so we know how to manage multi-variable

to manage multi-variables, we introduce matrix.

x * w = y

Now we just think dimension.

about expression

lecture(theory) : H(x) = wx+b

implementation(tensorflow) : H(x) = wx+b

plus, Gradient descent is useful.

w:= w-dcost/dw