Andrew Of Machine Learning Week2

Multivariate Linear Regression

1.Multiple Features (multiple features) (n represents the number of features)

　　x is a vector, assuming the function becomes

　　

　　It can be understood that θ is also a vector, hθ(x)=θ^T * x (transposition of θ*x)

　　

2.Gradient Descent for Multiple Variables

 

　　(Feature Scaling) Feature scaling