Univariate Linear Regression Model
Number of samples m Input variable x Output variable y Training sample (x, y) The i-th training sample ( , )
Hypothetical Function: Model Parameters
Cost function:
optimize the target:
algorithm:
1. Gradient descent
Specific solution:
2. Normal equation method