Solution 9.1

Perform the following steps to complete the activity:

1. For this activity, all you will need is the pandas library, some modules from sklearn, and numpy. Load them in the first cell of the notebook:

   import pandas as pd
   import numpy as np
   from sklearn.model_selection import train_test_split
   from sklearn.preprocessing import StandardScaler
   from sklearn.linear_model import LinearRegression as OLS
   from sklearn.metrics import mean_squared_error

2. Use the power_plant.csv dataset: 'Datasets\\power_plant.csv'. Read the data into a pandas DataFrame, print out the shape, and list the first five rows.

The independent variables are as follows:

• AT – ambient temperature
• V – exhaust vacuum level
• AP – ambient pressure
• RH – relative humidity

The dependent variable is the following:

• EP – electrical power produced

  power_data = pd.read_csv('Datasets\\power_plant.csv')
  print(power_data.shape...