
Linear Regression with Multiple Features
The screenshot below taken from https://www.coursera.org/learn/machinelearning/home/week/2 Enable gradient descent to run much faster : Feature Scaling

Cost Function
The first important step to apply linear regression is to define the cost function.Cost function will tell us how well/how fit the model is doing.We should look for more suitable w and b values based on the result. We are going to want to find values of w and b that make the cost function […]

Linear Regression
To train the model:You feed the training set (both the input features and the output targets) to your learning algorithm.Then your supervised learning algorithm will produce some function (f). f is called the model.Function takes a new input x and Estimates or makes prediction (y hat) for y. Here, we randomly gave the values w […]