Problem Statement
As in the lecture, you will use the motivating example of housing price prediction.
This lab will use a simple data set with only two data points - a house with 1000 square feet(sqft) sold for $300,000 and a house with 2000 square feet sold for $500,000. These two points will constitute our data or training set. In this lab, the units of size are 1000 sqft and the units of price are 1000s of dollars.
| Size (1000 sqft) | Price (1000s of dollars) |
|---|---|
| 1.0 | 300 |
| 2.0 | 500 |
You would like to fit a linear regression model (shown above as the blue straight line) through these two points, so you can then predict price for other houses - say, a house with 1200 sqft.
Please run the following code cell to create your x_train and y_train variables. The data is stored in one-dimensional NumPy arrays.
In [5]:
x_train is the input variable (size in 1000 square feet)
y_train is the target (price in 1000s of dollars)
x_train = np.array([1.0, 2.0])
y_train = np.array([300.0, 500.0])
print(f"x_train = {x_train}")
print(f"y_train = {y_train}")
--------------------------------------------------------------------------- NameError Traceback (most recent call last) in 1 # x_train is the input variable (size in 1000 square feet) 2 # y_train is the target (price in 1000s of dollars) ----> 3 x_train = np.array([1.0, 2.0]) 4 y_train = np.array([300.0, 500.0]) 5 print(f"x_train = {x_train}") NameError: name ‘np’ is not defined. Why am I getting an error code?
