In the topic "Simple linear regression" you've learned how to calculate regression coefficients, intercepts, and make predictions by hand. Now you can use sklearn to make predictions. Let's take a dataset from the topic "Simple linear regression":
| Cost of advertising campaign, $ | Number of new customers |
|---|---|
| 4 | 2 |
| 6 | 2 |
| 8 | 3 |
| 10 | 5 |
| 12 | 5 |
| 14 | 6 |
| 16 | 6 |
Build a linear regression model and predict the number of new customers for a 23$ spent on the advertising campaign. Insert the result in the answer field.
Tip: Use np.array([23]).reshape(1, 1) or just [[23]] to make 2D array from a scalar.