# 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?