We will again use our diamonds dataset. Although this is a small dataset and MLP is perhaps a model that is too complicated for this problem, there is no reason we could not use an MLP to solve it; in addition to this, remember that back when we defined the hypothetical problem, we established that the stakeholders wanted a model that was as accurate as possible in their predictions, so let's see how accurate we can get with an MLP. As always, let's import the libraries we will use:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import os
%matplotlib inline
Now, since we are beginning from scratch, load and prepare the dataset:
DATA_DIR = '../data'
FILE_NAME = 'diamonds.csv'
data_path = os.path.join(DATA_DIR, FILE_NAME)
diamonds = pd.read_csv(data_path)
## Preparation done from Chapter...
