Imports of the 3rd Notebook

wine_rating_predictor_imports3.py

# visualization and manipulation libraries
import matplotlib.pyplot as plt
import seaborn as sns
from IPython.core.pylabtools import figsize
import pandas as pd
import numpy as np
pd.set_option('display.max_columns', 60)

%matplotlib inline
# to display visuals in the notebook

%config InlineBackend.figure_format='retina'
#to enable high resolution plots

# feature prepocessing and split
from sklearn.metrics import mean_squared_error

# machine Learning Models
from sklearn.ensemble import RandomForestRegressor

# to load machine learning model
import pickle

# to visualize a decision tree
import sklearn.tree as tree
import pydotplus
from sklearn.externals.six import StringIO
from IPython.display import Image

# LIME to explain predictions
import lime 
import lime.lime_tabular

# to bypass warnings in section regarding previous imports
import warnings
warnings.filterwarnings('ignore')